Methods of lowering the error rate of massively parallel dna sequencing using duplex consensus sequencing

ABSTRACT

Next Generation DNA sequencing promises to revolutionize clinical medicine and basic research. However, while this technology has the capacity to generate hundreds of billions of nucleotides of DNA sequence in a single experiment, the error rate of approximately 1% results in hundreds of millions of sequencing mistakes. These scattered errors can be tolerated in some applications but become extremely problematic when “deep sequencing” genetically heterogeneous mixtures, such as tumors or mixed microbial populations. To overcome limitations in sequencing accuracy, a method Duplex Consensus Sequencing (DCS) is provided. This approach greatly reduces errors by independently tagging and sequencing each of the two strands of a DNA duplex. As the two strands are complementary, true mutations are found at the same position in both strands. In contrast, PCR or sequencing errors will result in errors in only one strand. This method uniquely capitalizes on the redundant information stored in double-stranded DNA, thus overcoming technical limitations of prior methods utilizing data from only one of the two strands.

PRIORITY CLAIM

This application is a continuation of U.S. patent application Ser. No.17/448,985, filed Sep. 27, 2021, which is a continuation of U.S. patentapplication Ser. No. 16/119,471, filed Aug. 31, 2018, now U.S. Pat. No.11,130,996, which is a continuation of U.S. patent application Ser. No.15/660,785, filed Jul. 26, 2017, now U.S. Pat. No. 10,287,631, which isa continuation of U.S. patent application Ser. No. 14/386,800, filedSep. 20, 2014, now U.S. Pat. No. 9,752,188, which is a U.S. nationalstage application of International Application No. PCT/US2013/032665,filed Mar. 15, 2013, which claims priority to U.S. Provisional PatentApplication No. 61/613,413, filed Mar. 20, 2012; U.S. Provisional PatentApplication No. 61/625,623, filed Apr. 17, 2012; and U.S. ProvisionalPatent Application No. 61/625,319, filed Apr. 17, 2012; the subjectmatter of all of which is hereby incorporated by reference as if fullyset forth herein.

STATEMENT OF GOVERNMENT INTEREST

This invention was made with government support under Grant Nos.F30AG033485, RO1CA102029 and RO1CA115802 awarded by the NationalInstitutes of Health. The government has certain rights in theinvention.

SEQUENCE LISTING

This application contains an ST.26 compliant Sequence Listing, which issubmitted concurrently in xml format via EFS-Web or Patent Center and ishereby incorporated by reference in its entirety. The .xml copy, createdon Sep. 12, 2023 is named Sequence Listing 072227-8043US33.xml and is10,000 bytes in size.

BACKGROUND

The advent of massively parallel DNA sequencing has ushered in a new eraof genomic exploration by making simultaneous genotyping of hundreds ofbillions of base-pairs possible at small fraction of the time and costof traditional Sanger methods [1]. Because these technologies digitallytabulate the sequence of many individual DNA fragments, unlikeconventional techniques which simply report the average genotype of anaggregate collection of molecules, they offer the unique ability todetect minor variants within heterogeneous mixtures [2].

This concept of “deep sequencing” has been implemented in a varietyfields including metagenomics [3, 4], paleogenomics [5], forensics [6],and human genetics [7, 8] to disentangle subpopulations in complexbiological samples. Clinical applications, such prenatal screening forfetal aneuploidy [9, 10], early detection of cancer and monitoring itsresponse to therapy [12, 13] with nucleic acid-based serum biomarkers,are rapidly being developed. Exceptional diversity within microbial [14,15] viral [16-18] and tumor cell populations [19, 20] has beencharacterized through next-generation sequencing, and manylow-frequency, drug-resistant variants of therapeutic importance havebeen so identified [12, 21, 22]. Previously unappreciatedintra-organismal mosasism in both the nuclear and mitochondrial [24, 25]genome has been revealed by these technologies, and such somaticheterogeneity, along with that arising within the adaptive immune system[13], may be an important factor in phenotypic variability of disease.

Deep sequencing, however, has limitations. Although, in theory, DNAsubpopulations of any size should be detectable when deep sequencing asufficient number of molecules, a practical limit of detection isimposed by errors introduced during sample preparation and sequencing.PCR amplification of heterogeneous mixtures can result in populationskewing due to stoichastic and non-stoichastic amplification biases andlead to over- or under-representation of particular variants [26].Polymerase mistakes during pre-amplification generate point mutationsresulting from base mis-incorporations and rearrangements due totemplate switching [26, 27]. Combined with the additional errors thatarise during cluster amplification, cycle sequencing and image analysis,approximately 1% of bases are incorrectly identified, depending on thespecific platform and sequence context [2, 28]. This background level ofartifactual heterogeneity establishes a limit below which the presenceof true rare variants is obscured [29].

A variety of improvements at the level of biochemistry [30-32] and dataprocessing [19, 21, 28, 32, 33] have been developed to improvesequencing accuracy. The ability to resolve subpopulations below 0.1%,however, has remained elusive. Although several groups have attempted toincrease sensitivity of sequencing, several limitations remain. Forexample techniques whereby DNA fragments to be sequenced are eachuniquely tagged [34, 35] prior to amplification [36-41] have beenreported. Because all amplicons derived from a particular startingmolecule will bear its specific tag, any variation in the sequence orcopy number of identically tagged sequencing reads can be discounted astechnical error. This approach has been used to improve countingaccuracy of DNA [38, 39, 41] and RNA templates [37, 38, 40] and tocorrect base errors arising during PCR or sequencing [36, 37, 39]. Kindeet. al. reported a reduction in error frequency of approximately 20-foldwith a tagging method that is based on labeling single-stranded DNAfragments with a primer containing a 14 bp degenerate sequence. Thisallowed for an observed mutation frequency of ˜0.001% mutations/bp innormal human genomic DNA [36]. Nevertheless, a number of highlysensitive genetic assays have indicated that the true mutation frequencyin normal cells is likely to be far lower, with estimates ofper-nucleotide mutation frequencies generally ranging from 10-9 to 10-11[42]. Thus, the mutations seen in normal human genomic DNA by Kinde etal. are likely the result of significant technical artifacts.

Traditionally, next-generation sequencing platforms rely upon generationof sequence data from a single strand of DNA. As a consequence,artifactual mutations introduced during the initial rounds of PCRamplification are undetectable as errors—even with tagging techniques—ifthe base change is propagated to all subsequent PCR duplicates. Severaltypes of DNA damage are highly mutagenic and may lead to this scenario.Spontaneous DNA damage arising from normal metabolic processes resultsin thousands of damaging events per cell per day [43]. In addition todamage from oxidative cellular processes, further DNA damage isgenerated ex vivo during tissue processing and DNA extraction [44].These damage events can result in frequent copying errors by DNApolymerases: for example a common DNA lesion arising from oxidativedamage, 8-oxo-guanine, has the propensity to incorrectly pair withadenine during complementary strand extension with an overall efficiencygreater than that of correct pairing with cytosine, and thus cancontribute a large frequency of artifactual G→T mutations [45].Likewise, deamination of cytosine to form uracil is a particularlycommon event which leads to the inappropriate insertion of adenineduring PCR, thus producing artifactual C→J mutations with a frequencyapproaching 100% [46].

It would be desirable to develop an approach for tag-based errorcorrection, which reduces or eliminates artifactual mutations arisingfrom DNA damage, PCR errors, and sequencing errors; allows rare variantsin heterogeneous populations to be detected with unprecedentedsensitivity; and which capitalizes on the redundant information storedin complexed double-stranded DNA.

SUMMARY

In one embodiment, a single molecule identifier (SMI) adaptor moleculefor use in sequencing a double-stranded target nucleic acid molecule isprovided. Said SMI adaptor molecule includes a single moleculeidentifier (SMI) sequence which comprises a degenerate orsemi-degenerate DNA sequence; and an SMI ligation adaptor that allowsthe SMI adaptor molecule to be ligated to the double-stranded targetnucleic acid sequence. The SMI sequence may be single-stranded ordouble-stranded. In some embodiments, the double-stranded target nucleicacid molecule is a double-stranded DNA or RNA molecule.

In another embodiment, a method of obtaining the sequence of adouble-stranded target nucleic acid is provided (also known as DuplexConsensus Sequencing or DCS) is provided. Such a method may includesteps of ligating a double-stranded target nucleic acid molecule to atleast one SMI adaptor molecule to form a double-stranded SMI-targetnucleic acid complex; amplifying the double-stranded SMI-target nucleicacid complex, resulting in a set of amplified SMI-target nucleic acidproducts; and sequencing the amplified SMI-target nucleic acid products.

In some embodiments, the method may additionally include generating anerror-corrected double-stranded consensus sequence by (i) grouping thesequenced SMI-target nucleic acid products into families of pairedtarget nucleic acid strands based on a common set of SMI sequences; and(ii) removing paired target nucleic acid strands having one or morenucleotide positions where the paired target nucleic acid strands arenon-complementary (or alternatively removing individual nucleotidepositions in cases where the sequence at the nucleotide position underconsideration disagrees among the two strands). In further embodiments,the method confirms the presence of a true mutation by (i) identifying amutation present in the paired target nucleic acid strands having one ormore nucleotide positions that disagree; (ii) comparing the mutationpresent in the paired target nucleic acid strands to the error correcteddouble-stranded consensus sequence; and (iii) confirming the presence ofa true mutation when the mutation is present on both of the targetnucleic acid strands and appears in all members of a paired targetnucleic acid family.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an overview of Duplex Consensus Sequencing. Sheareddouble-stranded DNA that has been end-repaired and T-tailed is combinedwith A-tailed SMI adaptors and ligated according to one embodiment.Because every adaptor contains a unique, double-stranded, complementaryn-mer random tag on each end (n-mer=12 bp according to one embodiment),every DNA fragment becomes labeled with two distinct SMI sequences(arbitrarily designated a and 13 in the single capture event shown).After size-selecting for appropriate length fragments, PCR amplificationwith primers containing Illumina flow-cell-compatible tails is carriedout to generate families of PCR duplicates. By virtue of the asymmetricnature of adapted fragments, two types of PCR products are produced fromeach capture event. Those derived from one strand will have the α SMIsequence adjacent to flow-cell sequence 1 and the 13 SMI sequenceadjacent to flow cell sequence 2. PCR products originating from thecomplementary strand are labeled reciprocally.

FIG. 2 illustrates Single Molecule Identifier (SMI) adaptor synthesisaccording to one embodiment. Oligonucleotides are annealed and thecomplement of the degenerate lower arm sequence (N's) plus adjacentfixed bases is produced by polymerase extension of the upper strand inthe presence of all four dNTPs. After reaction cleanup, complete adaptorA-tailing is ensured by extended incubation with polymerase and dATP.

FIG. 3 illustrates error correction through Duplex Consensus Sequencing(DCS) analysis according to one embodiment. (a-c) shows sequence reads(brown) sharing a unique set of SMI tags are grouped into pairedfamilies with members having strand identifiers in either the αβ or βαorientation. Each family pair reflects one double-stranded DNA fragment.(a) shows mutations (spots) present in only one or a few family membersrepresenting sequencing mistakes or PCR-introduced errors occurring latein amplification. (b) shows mutations occurring in many or all membersof one family in a pair representing mutations scored on only one of thetwo strands, which can be due to PCR errors arising during the firstround of amplification such as might occur when copying across sites ofmutagenic DNA damage. (c) shows true mutations (* arrow) present on bothstrands of a captured fragment appear in all members of a family pair.While artifactual mutations may co-occur in a family pair with a truemutation, these can be independently identified and discounted whenproducing (d) an error-corrected consensus sequence (i.e., singlestranded consensus sequence) (+ arrow) for each duplex. (e) showsconsensus sequences from all independently captured, randomly shearedfragments containing a particular genomic site are identified and (f)compared to determine the frequency of genetic variants at this locuswithin the sampled population.

FIG. 4 illustrates an example of how a SMI sequence with n-mers of 4nucleotides in length (4-mers) are read by Duplex Consensus Sequencing(DCS) according to some embodiments. (A) shows the 4-mers with the PCRprimer binding sites (or flow cell sequences) 1 and 2 indicated at eachend. (B) shows the same molecules as in (A) but with the strandsseparated and the lower strand now written in the 5′-3′ direction. Whenthese molecules are amplified with PCR and sequenced, they will yieldthe following sequence reads: The top strand will give a read 1 file ofTAAC- and a read 2 file of GCCA-. Combining the read 1 and read 2 tagswill give TAACCGGA as the SMI for the top strand. The bottom strand willgive a read 1 file of CGGA- and a read 2 file of TAAC-. Combining theread 1 and read 2 tags will give CGGATAAC as the SMI for the bottomstrand. (C) illustrates the orientation of paired strand mutations inDCS. In the initial DNA duplex shown in FIGS. 4A and 4B, a mutation “x”(which is paired to a complementary nucleotide “y”) is shown on the leftside of the DNA duplex. The “x” will appear in read 1, and thecomplementary mutation on the opposite strand, “y,” will appear in read2. Specifically, this would appear as “x” in both read 1 and read 2data, because “y” in read 2 is read out as “x” by the sequencer owing tothe nature of the sequencing primers, which generate the complementarysequence during read 2.

FIG. 5 illustrates duplex sequencing of human mitochondrial DNA. (A)Overall mutation frequency as measured by a standard sequencingapproach, SSCS, and DCS. (B) Pattern of mutation in human mitochondrialDNA by a standard sequencing approach. The mutation frequency (verticalaxis) is plotted for every position in the ˜16-kb mitochondrial genome.Due to the substantial background of technical error, no obviousmutational pattern is discernible by this method. (C) DCS analysiseliminates sequencing artifacts and reveals the true distribution ofmitochondrial mutations to include a striking excess adjacent to themtDNA origin of replication. (D) SSCS analysis yields a large excess ofG→T mutations relative to complementary C→A mutations, consistent withartifacts from damaged-induced 8-oxo-G lesions during PCR. Allsignificant (P<differences between paired reciprocal mutationfrequencies are noted. (E) DCS analysis removes the SSCS strand bias andreveals the true mtDNA mutational spectrum to be characterized by anexcess of transitions.

FIG. 6 shows that consensus sequencing removes artifactual sequencingerrors as compared to Raw Reads. Duplex Consensus Sequencing (DCS)results in an approximately equal number of mutations as the referenceand single strand consensus sequencing (SSCS).

FIG. 7 illustrates duplex sequencing of M13mp2 DNA. (A) Single-strandconsensus sequences (SSCSs) reveal a large excess of G→A/C→J and G→T/C→Amutations, whereas duplex consensus sequences (DCSs) yield a balancedspectrum. Mutation frequencies are grouped into reciprocal mispairs, asDCS analysis only scores mutations present in both strands of duplexDNA. All significant (P<0.05) differences between DCS analysis and theliterature reference values are noted. (B) Complementary types ofmutations should occur at approximately equal frequencies within a DNAfragment population derived from duplex molecules. However, SSCSanalysis yields a excess of G→T mutations relative to C→A mutations andan 11-fold excess of C→J mutations relative to G→A mutations. Allsignificant (P<0.05) differences between paired reciprocal mutationfrequencies are noted.

FIG. 8 shows the effect of DNA damage on the mutation spectrum. DNAdamage was induced by incubating purified M13mp2 DNA with hydrogenperoxide and FeSO4. (A) SSCS analysis reveals a further elevation frombaseline of G→T mutations, indicating these events to be the artifactualconsequence of nucleotide oxidation. All significant (P<0.05) changesfrom baseline mutation frequencies are noted. (B) Induced DNA damage hadno effect on the overall frequency or spectrum of DCS mutations.

FIG. 9 shows duplex sequencing results in accurate recovery ofspiked-control mutations. A series of variants of M13mp2 DNA, eachharboring a known single-nucleotide substitution, were mixed in togetherat known ratios and the mixture was sequenced to ˜20,000-fold finaldepth. Standard sequencing analysis cannot accurately distinguishmutants present at a ratio of less than 1/100, because artifacturalmutations occurring at every position obscure the presence of lessabundant true mutations, rendering apparent recovery greater than 100%.Duplex consensus sequences, in contrast, accurately identify spiked-inmutations down to the lowest tested ratio of 1/10,000.

FIG. 10 is a Python Code that may used to carry out methods describedherein according to one embodiment.

DETAILED DESCRIPTION

Single molecule identifier adaptors and methods for their use areprovided herein. According to the embodiments described herein, a singlemolecule identifier (SMI) adaptor molecule is provided. Said SMI adaptormolecule is double stranded, and may include a single moleculeidentifier (SMI) sequence, and an SMI ligation adaptor (FIG. 2 ).Optionally, the SMI adaptor molecule further includes at least two PCRprimer binding sites, at least two sequencing primer binding sites, orboth.

The SMI adaptor molecule may form a “Y-shape” or a “hairpin shape.” Insome embodiments, the SMI adaptor molecule is a “Y-shaped” adaptor,which allows both strands to be independently amplified by a PCR methodprior to sequencing because both the top and bottom strands have bindingsites for PCR primers FC1 and FC2 as shown in the examples below. Aschematic of a Y-shaped SMI adaptor molecule is also shown in FIG. 2 . AY-shaped SMI adaptor requires successful amplification and recovery ofboth strands of the SMI adaptor molecule. In one embodiment, amodification that would simplify consistent recovery of both strandsentails ligation of a Y-shaped SMI adaptor molecule to one end of a DNAduplex molecule, and ligation of a “U-shaped” linker to the other end ofthe molecule. PCR amplification of the hairpin-shaped product will thenyield a linear fragment with flow cell sequences on either end. DistinctPCR primer binding sites (or flow cell sequences FC1 and FC2) will flankthe DNA sequence corresponding to each of the two SMI adaptor moleculestrands, and a given sequence seen in Read 1 will then have the sequencecorresponding to the complementary DNA duplex strand seen in Read 2.Mutations are scored only if they are seen on both ends of the molecule(corresponding to each strand of the original double-stranded fragment),i.e. at the same position in both Read 1 and Read 2. This design may beaccomplished as described in the examples relating to double strandedSMI sequence tags.

In other embodiments, the SMI adaptor molecule is a “hairpin” shaped (or“U-shaped”) adaptor. A hairpin DNA product can be used for errorcorrection, as this product contains both of the two DNA strands. Suchan approach allows for reduction of a given sequencing error rate N to alower rate of N*N*(1/3), as independent sequencing errors would need tooccur on both strands, and the same error among all three possible basesubstitutions would need to occur on both strands. For example, theerror rate of 1/100 in the case of Illumina sequencing would be reducedto (1/100)*(1/100)*(1/3)=1/30,000.

An additional, more remarkable reduction in errors can be obtained byinclusion of a single-stranded SMI in either the hairpin adaptor or the“Y-shaped” adaptor will also function to label both of the two DNAstrands. Amplification of hairpin-shaped DNA may be difficult as thepolymerase must synthesize through a product containing significantregions of self-complementarity, however, amplification ofhairpin-shaped structures has already been established in the techniqueof hairpin PCR, as described below. Amplification using hairpin PCR isfurther described in detail in U.S. Pat. No. 7,452,699, the subjectmatter of which is hereby incorporated by reference as if fully setforth herein.

According to the embodiments described herein, the SMI sequence (or“tag”) may be a double-stranded, complementary SMI sequence or asingle-stranded SMI sequence. In some embodiments, the SMI adaptormolecule includes an SMI sequence (or “tag”) of nucleotides that isdegenerate or semi-degenerate. In some embodiments, the degenerate orsemi-degenerate SMI sequence may be a random degenerate sequence. Adouble-stranded SMI sequence includes a first degenerate orsemi-degenerate nucleotide n-mer sequence and a second n-mer sequencethat is complementary to the first degenerate or semi-degeneratenucleotide n-mer sequence, while a single-stranded SMI sequence includesa first degenerate or semi-degenerate nucleotide n-mer sequence. Thefirst and/or second degenerate or semi-degenerate nucleotide n-mersequences may be any suitable length to produce a sufficiently largenumber of unique tags to label a set of sheared DNA fragments from asegment of DNA. Each n-mer sequence may be between approximately 3 to 20nucleotides in length. Therefore, each n-mer sequence may beapproximately 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19,20 nucleotides in length. In one embodiment, the SMI sequence is arandom degenerate nucleotide n-mer sequence which is 12 nucleotides inlength. A 12 nucleotide SMI n-mer sequence that is ligated to each endof a target nucleic acid molecule, as described in the Example below,results in generation of up to 4²⁴ (i.e., 2.8×10¹⁴) distinct tagsequences.

In some embodiments, the SMI tag nucleotide sequence may be completelyrandom and degenerate, wherein each sequence position may be anynucleotide. (i.e., each position, represented by “X,” is not limited,and may be an adenine (A), cytosine (C), guanine (G), thymine (T), oruracil (U)) or any other natural or non-natural DNA or RNA nucleotide ornucleotide-like substance or analog with base-pairing properties (e.g.,xanthosine, inosine, hypoxanthine, xanthine, 7-methylguanine,7-methylguanosine, 5,6-dihydrouracil, 5-methylcytosine, dihydouridine,isocytosine, isoguanine, deoxynucleosides, nucleosides, peptide nucleicacids, locked nucleic acids, glycol nucleic acids and threose nucleicacids). The term “nucleotide” as described herein, refers to any and allnucleotide or any suitable natural or non-natural DNA or RNA nucleotideor nucleotide-like substance or analog with base pairing properties asdescribed above. In other embodiments, the sequences need not containall possible bases at each position. The degenerate or semi-degeneraten-mer sequences may be generated by a polymerase-mediated methoddescribed in the Example below, or may be generated by preparing andannealing a library of individual oligonucleotides of known sequence.Alternatively, any degenerate or semi-degenerate n-mer sequences may bea randomly or non-randomly fragmented double stranded DNA molecule fromany alternative source that differs from the target DNA source. In someembodiments, the alternative source is a genome or plasmid derived frombacteria, an organism other than that of the target DNA, or acombination of such alternative organisms or sources. The random ornon-random fragmented DNA may be introduced into SMI adaptors to serveas variable tags. This may be accomplished through enzymatic ligation orany other method known in the art.

In some embodiments, the SMI adaptor molecules are ligated to both endsof a target nucleic acid molecule, and then this complex is usedaccording to the methods described below. In certain embodiments, it isnot necessary to include n-mers on both adapter ends, however, it ismore convenient because it means that one does not have to use twodifferent types of adaptors and then select for ligated fragments thathave one of each type rather than two of one type. The ability todetermine which strand is which is still possible in the situationwherein only one of the two adaptors has a double-stranded SMI sequence.

In some embodiments, the SMI adaptor molecule may optionally include adouble-stranded fixed reference sequence downstream of the n-mersequences to help make ligation more uniform and help computationallyfilter out errors due to ligation problems with improperly synthesizedadaptors. Each strand of the double-stranded fixed reference sequencemay be 4 or 5 nucleotides in length sequence, however, the fixedreference sequence may be any suitable length including, but not limitedto 3, 4, 5 or 6 nucleotides in length.

The SMI ligation adaptor may be any suitable ligation adaptor that iscomplementary to a ligation adaptor added to a double-stranded targetnucleic acid sequence including, but not limited to a T-overhang, anA-overhang, a CG overhang, a blunt end, or any other ligatable sequence.In some embodiments, the SMI ligation adaptor may be made using a methodfor A-tailing or T-tailing with polymerase extension; creating anoverhang with a different enzyme; using a restriction enzyme to create asingle or multiple nucleotide overhang, or any other method known in theart.

According to the embodiments described herein, the SMI adaptor moleculemay include at least two PCR primer or “flow cell” binding sites: aforward PCR primer binding site (or a “flow cell 1” (FC1) binding site);and a reverse PCR primer binding site (or a “flow cell 2” (FC2) bindingsite). The SMI adaptor molecule may also include at least two sequencingprimer binding sites, each corresponding to a sequencing read.Alternatively, the sequencing primer binding sites may be added in aseparate step by inclusion of the necessary sequences as tails to thePCR primers, or by ligation of the needed sequences. Therefore, if adouble-stranded target nucleic acid molecule has an SMI adaptor moleculeligated to each end, each sequenced strand will have two reads—a forwardand a reverse read.

Double-Stranded SMI Sequences

Adaptor 1 (shown below) is a Y-shaped SMI adaptor as described above(the SMI sequence is shown as X's in the top strand (a 4-mer), with thecomplementary bottom strand sequence shown as Y's):

Adaptor 2 (shown below) is a hairpin (or “U-shaped”) linker:

Following ligation of both adaptors to a double-stranded target nucleicacid, the following is structure is obtained:

When melted, the product will be of the following form (where “linker”is the sequence of adaptor 2):

-   -   FC1-XXXX-DNA-linker-DNA′-YYYY-FC2

This product is then PCR amplified. The reads will yield:

Read 1:

-   -   XXXX-DNA-

Read 2 (note that read 2 is seen as the complement of the basessequenced:)

-   -   XXXX-DNA-

The sequences of the two duplex strands seen in the two sequence readsmay then be compared, and sequence information and mutations will bescored only if the sequence at a given position matches in both of thereads.

This approach does not strictly require the use of an SMI tag, as thesheared ends can be used as identifiers to differentiate uniqueindividual molecules from PCR duplicates. Thus the same concept wouldapply if one used any standard sequencing adaptor as “Adaptor 1” and theU-shaped linker as “Adaptor 2.” However described below, there are alimited number of shear points flanking any given genomic position andthus the power to sequence deeply is increased via inclusion of the SMItag. A hybrid method using a combination of sheared ends and a shortern-mer tag (such as 1 or 2 or 3 or 4 or more degenerate orsemi-degenerate bases) in the adaptor may also serve as unique molecularidentifiers. Another design may include use of any sequencing adaptor(such as one lacking an n-mer tag) in conjunction with an n-mer tag thatis incorporated into the U-shaped linker molecule. Such a design wouldbe of the following form (where X and Y represent complementarydegenerate or semi-degenerate nucleotides):

Synthesis of such a design may be obtained in a number of ways, forexample synthesizing a set of hairpin oligonucleotides in which eachindividual oligonucleotide encodes a complementary n-mer sequence, oralternatively by using a DNA polymerase to carry out extension from thefollowing product (where X's represent degenerate nucleotides):

Inclusion of the SMI tag is also extremely useful for identifyingcorrect ligation products, as the assay uses two distinct adaptors. Thiswill yield multiple possible ligation products:

Product I. Adaptor 1-DNA-Adaptor 2, which yields the desired product:

Product II. Adaptor 1-DNA-Adaptor 1. This will result in the DNA beingamplified as two separate strands, i.e. as occurs in the DCS approachdescribed elsewhere in this document (the second copy of Adaptor 1 isshown below with the SMI as AAA-BBB to emphasize that every DCS adaptorhas a distinct SMI sequence)

Product III. Adaptor 2-DNA-Adaptor 2. This will result in anon-amplifiable circular product shown below:

Product III is non-amplifiable, given the absence of primer bindingsites and thus will not be present in the final DNA sequences. Thus onlyProduct II needs to be avoided. The formation of Product II can beminimized in the ligation step by using an excess of Adaptor 2 (relativeto Adaptor 1). Then primarily Products I and III will be obtained, withminimal formation of Product II. Additionally, a variety of biochemicalmeans of enriching for products containing adaptor 2 are possible suchas using affinity probes that are complementary to the hairpin loopsequence itself. Product I results in the same SMI sequence in both theRead 1 and Read 2 sequence reads. In the example depicted above, ProductI sequences can thus be identified by virtue of having matching SMIs ofthe form XXXX in Read 1 and XXXX in Read 2.

By contrast, in the case of Product II, the SMI sequences on either endof the sequenced molecule will arise from distinct DCS adaptors havingdifferent SMI sequences. In the example shown above, Product IIsequences yield SMIs of the form XXXX (Read 1)-BBB (Read 2) uponsequencing of the top strand, and BBBB (Read 1)-XXXX (Read 2) uponsequencing of the bottom strand. Thus Product II sequences can be easilyidentified and computationally removed from the final sequence data.

Data resulting from Product II is useful, because Product II correspondsto the product analyzed under the approach detailed in the Examplebelow. Product I contains a self-complementary hairpin sequence that canimpair polymerase extension during amplification, however, this type ofamplification has already been enabled in the technique of “Hairpin PCR”which involves linking of the two strands followed by amplification withgene-specific primers. Amplification conditions that are compatible withamplification of hairpin DNA are thus already established. Moreover,ligation and amplification with circularizing “linkers” (i.e. hairpinlinkers affixed to both ends of a fragment) has been demonstrated as astep in the Pacific Biosciences sample preparation workflow [49]. As thesequence of the linker itself does not matter in the workflow, thepublished linker sequences from either of these references would beadequate for use in the assay.

In some aspects of some embodiments, deliberate ligation of “U-shaped”adaptors or hairpin linkers containing 1) a double-stranded n-mer (orother form of degenerate or semi-degenerate double-stranded tag asenumerated above) plus 2) primer binding sites to both ends of acaptured fragment may be desireable. Producing closed circles ofcaptured material may help facilitate removal of non-captured DNA byexonuclease digestion given that circularized DNA will be protected fromdigestion by such enzymes. Additionally, closed circles may bepre-amplified using rolling circle amplification or serve as thesubstrate for continuous loop sequencing [49]. Recognition sites forrestriction endonuclease digestion could be engineered into theseadaptors to render closed loops open once again if more convenient forsubsequent steps.

In another embodiment, flow cell sequences or PCR binding sites, againdenoted as FC1 and FC2, may be included in both the PCR primers and thehairpin linker adaptor, as well as a ligatable sequence on the end ofthe hairpin linker (denoted as L below). The hairpin linker adaptor mayadditionally include one or more cleavable sequences, denoted as R inthe example below (the R may be any appropriate restriction enzymetarget sequence, or any other cleavable sequence). Such a hairpin linkerdesign is shown below:

The target DNA with ligation site denoted as L is as follows:

-   -   -DNA-L    -   -DNA′-L

Following ligation of the linker, the product may be amplified with PCRprimers as follows:

The resultant product will be of the form:

-   -   FC1-DNA-XXXX-FC2-R-R-FC1-YYYY-DNA′-FC2

After amplification of the product, the cleavage sites R may be cleavedto result in the following sequencable products:

-   -   FC1-DNA-XXXX-FC2        and    -   FC1-YYYY-DNA′-FC2

These products may then be sequenced directly. This design has theadvantage of allowing for targeted sequencing of a specific region ofthe genome, and furthermore avoids the need to sequence a hairpinproduct, as sequencing of a hairpin will be less efficient due to theself-complementarity present within the hairpin molecule.

Single-Stranded SMI Sequences

In one embodiment, a single-stranded SMI sequence is incorporated intothe single-stranded portion of the hairpin loop (regions of sequencecomplementarity are denoted as “=”). The SMI sequence is shown as fournucleotides in length in the following examples, but in practice an Nmerof any length, including approximately 3 to 20 nucleotides, willsuffice.

Ligation of the hairpin linker and a Y-shaped sequencing adaptor (withPCR primer binding sites labeled as FC1 and FC2) yields the followingproduct:

Melting and PCR amplification of this product yields the following DNAproduct:

-   -   FC1-DNA-NNNN-hairpin sequence-DNA′-FC2

Following PCR duplication of the product and formation of consensusreads based upon the shared SMI sequence among all the PCR duplicates,the sequences of the two strands (denoted DNA and DNA′) can then becompared to form a duplex consensus sequence.

In another embodiment, a single-stranded SMI is incorporated into amodified “Y-shaped” sequencing adaptor in which PCR primer binding sitesare located at the sites labeled FC1 and FC2 (regions of sequencecomplementarity are depicted as)

It will be apparent to one skilled in the art that a single-stranded SMIsequence tag can be located in any of several positions within eitherthe sequencing adaptor or the hairpin linker. The single-stranded SMIsequence tag can be synthesized as a random oligonucleotide sequence, orcan be sequenced as a set of fixed sequences by synthesis on an array,or by any other suitable method known in the art.

Methods for Synthesis of Complementary or Partially Complementary DoubleStranded SMI Tags

SMI adaptors molecules containing a double-stranded, complementary,degenerate or semi-degenerate SMI tag can be made by any of a number ofmethods, including copying of a single-stranded SMI sequence by a DNApolymerase as described above or synthesis and annealing of twooligonucleotides containing complementary SMI sequences. An additionalmethod involves synthesizing a set of linear oligonucleotides which willself-anneal into the appropriate form. Inclusion of a cleavable linkerin each oligonucleotide will then allow for conversion of a “hairpinshaped” SMI adaptor molecule into a “Y-shaped” SMI adaptor molecule. Forexample, an oligonucleotide may be prepared of the following form:

-   -   5′-YYYY-U-XXXX-3′

In this schematic, X and Y represent complementary nucleotides, and Uindicates a cleavable linker, such as uracil (which can be cleaved bycombined treatment with uracil DNA glycosylase and apurinicendonuclease), although any other cleavable linker will suffice. Theoligonucleotide may be designed with appropriate regions ofself-complementarity to anneal into the following form:

The linker (e.g. uracil) may then be cleaved, yielding a DCS adaptor:

A double-stranded SMI hairpin linker can be constructed by an analogousmethod but without the need for a cleavable linker. For example, a setof nucleotides of known sequence where X and Y represent thecomplementary SMI sequences can be synthesized on an array, or by anyother suitable method known in the art:

-   -   5′-XXXX-YYYY=3′

This oligonucleotide can then self-anneal to form a hairpin linker withcomplementary SMI sequences.

Any of the oligonucleotides described above can also include anyligatable sequence as overhangs on either the 5′ or 3′ end, or can beused for blunt end ligation.

DCS SMI Adaptor Molecules May Include Sequences to Allow for TargetedDNA Capture

DCS SMI adaptor molecules contain ligatable ends to allow attachment ofthe adaptor to a target DNA molecule. In some embodiments, the ligatableend may be complementary to a DNA overhang on the target DNA, forexample, one generated by digestion of target DNA with a restrictionendonuclease. Selective ligation of the adaptor to the targeted DNAcontaining the matching Single-stranded overhanging DNA sequence willthen allow for partial purification of the targeted DNA. A non-limitingexample of this embodiment is shown above. In some embodiments, the DCSSMI adaptor molecule, or a hairpin linker SMI adaptor molecule, mayadditionally contain modifications such as biotin to facilitate affinitypurification of target DNA that has ligated to the adaptor.

In another embodiments, specific PCR primers can selectively amplifyspecific regions of genome when the adaptor that is ligated to the otherend of the molecule is a hairpin (or “U-shape”). Alternatively, thismethod may be used with or without the need for this cleavable hairpinsequence.

Preparation of DNA for Duplex Consensus Sequencing May be Performed byPCR Amplification in a Hairpin Structure

Another embodiment involves fragmentation of DNA at defined regions, forexample by treatment of DNA with a site-specific restrictionendonuclease or a mixture of such endonucleases, followed by annealingof a hairpin oligonucleotide linker, and amplification of the hairpincomplex with PCR primers sufficient for amplification of the desired DNAsequence. Annealing of the hairpin linker to only one of the two ends ofthe DNA duplex could be accomplished by using different restrictionenzymes to cut on either end of the target duplex, and then having thehairpin linker ligation adaptor being ligatable to only one of the tworesultant ligatable ends.

The example shown below indicates forward and reverse PCR primers(labeled 1 and 2) in conjunction with a hairpin linker to allow linkedamplification of both complementary strands of duplex DNA. Suchamplification, in conjunction with a single-stranded or double-strandedSMI sequence, would allow for targeted amplification and high accuracydeep sequencing of a specific sequence of interest. In the schematicshown below, a single-stranded SMI sequence is incorporated into PCRprimer FC1. It would be apparent to one skilled in the art that the SMIsequence could also be incorporated in primer FC2, or in the hairpinlinker.

Amplified product:

-   -   FC1NNNN DNA-hairpin sequence-DNA′FC2

This product can then be subjected to consensus sequencing analysis. TheSMI sequence allows one to group together products of PCR amplificationarising from a single molecule of duplex DNA. The sequences of the twoDNA strands can then be compared for error correction.

Uses of SMI Adapter Molecules

The SMI adaptor molecules described herein have several uses. In someembodiments, the SMI adaptor molecules described herein may be used inmethods to obtain the sequence or other sequence-related information ofa double-stranded target nucleic acid molecule. According to theembodiments described herein, the term “double-stranded target nucleicacid molecule” includes a double-stranded DNA molecule or adouble-stranded RNA molecule. Thus, the SMI adaptor molecules andmethods of use described herein are applicable to genotyping and otherapplications related to sequencing of DNA molecules, but are alsoapplicable to RNA sequencing applications such as for sequencing ofdouble-stranded RNA viruses. Methods for sequencing RNA may include anyof the embodiments described herein with respect to DNA sequencing, andvice-versa. For example, any double stranded target nucleic acidmolecule may be ligated to an SMI adaptor molecule which includes adouble-stranded RNA or DNA n-mer tag and an RNA or DNA ligation adapteras described above. Methods exist for directly sequencing RNA [51];alternatively, the ligated product may be reverse transcribed into DNA,and then sequenced as a double-stranded target DNA molecule.

In one embodiment, the double-stranded target nucleic acid molecule maybe a sheared double-stranded DNA or RNA fragment. The sheared target DNAor RNA molecule may be end repaired and a double-stranded target nucleicacid sequence ligation adaptor may be added to each end of the shearedtarget DNA or RNA molecule. The double-stranded target nucleic acidsequence ligation adaptor may be any suitable ligation adaptor that iscomplementary to the SMI ligation adaptor described above including, butnot limited to a T-overhang, an A-overhang, a CG overhang, blunt end orany other ligatable sequence. In some embodiments, the double-strandedtarget nucleic acid sequence ligation adaptor may be made using a methodfor A-tailing or T-tailing with polymerase extension; adding an overhangwith a different enzyme; using a restriction enzyme to create aligatable overhang; or any other method known in the art.

Methods to obtain the sequence or other sequence-related information ofa double-stranded target nucleic acid molecule may include a step ofligating the double-stranded target nucleic acid molecule to at leastone SMI adaptor molecule, such as those described above, to form adouble-stranded target nucleic acid complex. In one embodiment, each endof the double-stranded target nucleic acid molecule is ligated to an SMIadaptor molecule. The double-stranded target nucleic acid complex isthen amplified by a method known in the art (e.g., a PCR or non-PCRmethod known in the art), resulting in a set of uniquely labeled,amplified SMI-target nucleic acid products. These products are thensequenced using any suitable method known in the art including, but notlimited to, the Illumina sequencing platform, ABI SOliD sequencingplatform, Pacific Biosciences sequencing platform, 454 Life Sciencessequencing platform, Ion Torrent sequencing platform, Helicos sequencingplatform, and nanopore sequencing technology.

In certain embodiments, a method of generating an error correcteddouble-stranded consensus sequence is provided. Such a method, alsoreferred to as duplex consensus sequencing (DCS), allows for aquantitative detection of sites of DNA damage. DCS analysis facilitatesthe detection of DNA damage signatures, in that single stranded DNAmutations that are not present in the complementary strand can beinferred to be artifactual mutations arising from damaged nucleotides.Not only can one correct for these erroneous mutations, but the abilityto indirectly infer that damage is present on the DNA could be a usefulbiomarker (e.g. for cancer risk, cancer metabolic state, mutatorphenotype related to defective damage repair, carcinogen exposure,chronic inflammation exposure, individual-specific aging,neurodegenerative diseases etc). The ability to use differentpolymerases during the first round(s) of PCR to mis-incorporate atdamage sites could potentially add even more information. Besidespolymerases, other DNA modifying/repair enzymes could be used prior toamplification to convert damage of one sort that doesn't give a specificmutagenic signature into another sort that does with whatever polymeraseis used. Alternatively, DNA modifying/repair enzymes could be used toremove damaged bases, and one could sequence both strands of DNA bothwith and without the enzymatic treatment. Mutations in single-strandedDNA that are seen to be removed by the enzymatic treatment can thus beinferred to be arising due to DNA damage. This could be useful on humannuclear or mtDNA but also might also be useful with model organisms(mice, yeast, bacteria etc), treated with different new damaging agents,facilitating a screen for DNA damaging compounds that would be analogousto the widely used Ames test [52].

The method of generating an error corrected double-stranded consensussequence may include a first stage termed “single strand consensussequencing” (SSCS) followed by a second stage of duplex consensussequencing (DCS). Therefore, the method includes steps of taggingindividual duplex DNA molecules with an SMI adaptor molecule, such asthose described above; generating a set of PCR duplicates of the taggedDNA molecules by performing a suitable PCR method; creating a singlestrand consensus sequence from all of the PCR duplicates which arosefrom an individual molecule of single-stranded DNA. Each DNA duplexshould result in two single strand consensus sequences. The work throughthese three steps conclude the first stage and is termed SSCS.

The method of generating an error corrected double-stranded consensussequence further comprises the second stance that is termed DCS. The DCSstage includes steps of comparing the sequence of the two single strandconsensus sequences arising from a single duplex DNA molecule, andfurther reducing sequencing or PCR errors by considering only sites atwhich the sequences of both single-stranded DNA molecules are inagreement. The method that includes the first stage and the second stagetermed Duplex Consensus Sequencing (DCS).

The step of tagging of both strands of individual duplex DNA may beaccomplished by ligation of degenerate or semi-degenerate complementaryDNA sequences; as the complementary nature of the two strands of such atag sequence allows the two molecules to be grouped together for errorcorrection. Alternatively, as described above, the two duplex DNAstrands may be linked by ligation of a U-shaped SMI adaptor molecule,and the two DNA strands can thus both be tagged with a single-strandedSMI tag.

In the method described above, a set of sequenced SMI-DNA productsgenerated in the methods described above may be grouped into families ofpaired target nucleic acid strands based on a common set of SMIsequences. Then, the paired target nucleic acid strands can be filteredto remove nucleotide positions where the sequences seen on both of thepaired partner DNA strands are not complementary. This error correcteddouble-stranded consensus sequence may be used in a method forconfirming the presence of a true mutation (as opposed to a PCR error orother artifactual mutation) in a target nucleic acid sequence. Accordingto certain embodiments, such a method may include identifying one ormore mutations present in the paired target nucleic acid strands thathave one or more nucleotide positions that disagree between the twostrands, then comparing the mutation present in the paired targetnucleic acid strands to the error corrected double-stranded consensussequence. The presence of a true mutation is confirmed when the mutationis present on both of the target nucleic acid strands and also appear inall members of a pared target nucleic acid family.

The accuracy of current approaches to next-generation sequencing islimited due to their dependence on interrogating single-stranded DNA.This dependence makes potential sources of error such as PCRamplification errors and DNA damage fundamentally limiting. However, thecomplementary strands of a double-stranded DNA molecule (or “DNAduplex”) contain redundant sequencing information (i.e., one moleculereciprocally encoding the sequence information of its partner) which canbe utilized to eliminate such artifacts. Limitations related tosequencing single-stranded DNA (e.g., sequencing errors) may thereforebe overcome using the methods described herein. This is accomplished byindividually tagging and sequencing each of the two strands of adouble-stranded (or duplex) target nucleic acid molecule and comparingthe individual tagged amplicons derived from one half of adouble-stranded complex with those of the other half of the samemolecule. Duplex Consensus Sequencing (DCS), significantly lowers theerror rate of sequencing. In some embodiments, the DCS method may beused in methods for high sensitivity detection of rare mutant andvariant DNA as described further below.

As described above, one approach that has previously been reported forDNA sequencing involves incorporation of a random tag sequence into aPCR primer [36]. This approach results in an improvement in accuracyrelative to standard Illumina sequencing, but is fundamentally limitedin that it is based upon amplification and sequencing of single-strandedDNA and thus cannot overcome limitations in sensitivity owing tosingle-stranded DNA damage events. In the methods described herein, PCRduplicates are generated from a single strand of DNA, and the sequencesof the duplicates are compared. Mutations are scored only when they arepresent in multiple replicates of a single starting molecule. The DCSapproach overcomes the limitation of previous approaches by consideringboth DNA strands.

DNA damage should not be a limiting factor in DCS, because miscodingdamage events at a single base-pair position occur essentiallyexclusively on only one of the two DNA strands. For DNA damage to resultin an artifactual mutation in DCS, damage would need to be present atthe same nucleotide position on both strands. Even if complementarynucleotides in a duplex were both damaged, the damage would need toresult in complementary sequencing errors to result in mis-scoring of amutation. Likewise, spontaneous PCR errors would need to result incomplementary mutations at the same position on both strands; with afirst-round mutation frequency of Taq polymerase of approximately 10⁻⁵and three possible incorrect bases that could be mis-inserted, theprobability of two complementary PCR errors occurring would be10⁻⁵×10⁻⁵×1/3=3.3×10⁻¹¹

According to some embodiments, the sequencing method may be performedusing the Illumina or similar platforms including those enumerated abovewithout the use of SMI adaptor molecules, but instead by using therandom shear points of DNA as identifiers. For a given DNA sequence seenin sequencing read 1 with a specific set of shear points, the partnerstrand will be seen as a matching sequence in read two with identicalshear points. In practice, this approach is limited by the limitednumber of possible shear points that overlap any given DNA position.However, according to some embodiments, shear points of a target nucleicacid molecule may be used as unique identifiers to identifydouble-stranded (or duplex) pairs, resulting in an apparent errorfrequency at least as low as that seen with traditional sequencingmethods, but with a significantly lower loss of sequence capacity. Inother embodiments, DCS based on shear points alone may have a role forconfirmation that specific mutations of interest are true mutationswhich were indeed present in the starting sample (i.e. present in bothDNA strands), as opposed to being PCR or sequencing artifacts. Overall,however, DCS is most generally applicable when randomized, complementarydouble-stranded SMI sequences are used. A 24 nucleotide double-strandedSMI sequence was used in the Example described below, which may yield upto 4²⁴=2.8×10¹⁴ distinct double-stranded SMI sequences. Combininginformation regarding the shear points of DNA with the SMI tag sequencewould allow a shorter SMI to be used, thus minimizing loss of sequencingcapacity due to sequencing of the SMI itself.

In certain embodiments, the SMI adaptor molecules may also be used inmethods of single-molecule counting for accurate determination of DNA orRNA copy number [38]. Again, since the SMI tags are present in theadaptors, there are no altered steps required in library preparation,which is in contrast to other methods for using random tags forsingle-molecule counting. Single-molecule counting has a large number ofapplications including, but not limited to, accurate detection ofaltered genomic copy number (e.g., for sensitive diagnosis of geneticconditions such as trisomy 21 [47]), for accurate identification ofaltered mRNA copy number in transcriptional sequencing and chromatinimmunoprecipitation experiments, quantification of circulatingmicroRNAs, quantification of viral load of DNA or RNA viruses,quantification of microorganism abundance, quantification of circulatingneoplastic cells, counting of DNA-labeled molecules of any varietyincluding tagged antibodies or aptamers, and quantification of relativeabundances of different individual's genomes in forensic applications.

In another embodiment, the SMI adaptor molecules may be used in methodsfor unambiguous identification of PCR duplicates. In order to restrictsequencing analysis to uniquely sequenced DNA fragments, many sequencingstudies include a step to filter out PCR duplicates by using the shearpoints at the ends of DNA molecules to identify distinct molecules. Whenmultiple molecules exhibit identical shear points, all but one of themolecules are discarded from analysis under the assumption that themolecules represent multiple PCR copies of the same starting molecule.However sequence reads with identical shear points can also reflectdistinct molecules because there are a limited number of possible shearpoints at any given genomic location, and with increasing sequencingdepth, recurrent shear points are increasingly likely to be seen [48].Because the use of SMI tags (or “double-stranded SMI sequences”) allowsevery molecule to be uniquely labeled prior to PCR duplication, true PCRduplicates may be unambiguously identified by virtue of having a common(i.e., the same or identical) SMI sequence. This approach would therebyminimize the loss of data by overcoming the intrinsic limitations ofusing shear points to identify PCR duplicates.

Importantly, once SMI-containing adaptors are synthesized by astraightforward series of enzymatic steps or are produced throughsynthesis of a set of oligonucleotides containing complementary tagsequences, they may be substituted for standard sequencing adaptors.Thus, use of DCS does not require any significant deviations from thenormal workflow of sample preparation for Illumina DNA sequencing.Moreover, the DCS approach can be generalized to nearly any sequencingplatform because a double-stranded SMI tag can be incorporated intoother existing adaptors, or for sequencing approaches that do notrequire adaptors, a double-stranded SMI tag can be ligated onto duplexDNA sample prior to sequencing. The compatibility of DCS with existingsequencing workflows, the potential for greatly reducing the error rateof DNA sequencing, and the multitude of applications for thedouble-stranded SMI sequences validate DCS as a technique that may playa general role in next generation DNA sequencing.

The following examples are intended to illustrate various embodiments ofthe invention. As such, the specific embodiments discussed are not to beconstrued as limitations on the scope of the invention. It will beapparent to one skilled in the art that various equivalents, changes,and modifications may be made without departing from the scope ofinvention, and it is understood that such equivalent embodiments are tobe included herein. Further, all references cited in the disclosure arehereby incorporated by reference in their entirety, as if fully setforth herein.

EXAMPLES Example 1: Generation of SMI Adaptor Molecules and their Use inSequencing Double-Stranded Target DNA

Materials and Methods

Materials. Oligonucleotides were from IDT and were ordered as PAGEpurified. Klenow exo- was from NEB. T4 ligase was from Enzymatics.

DNA isolation. Genomic DNA was isolated from normal human colonic mucosaby sodium iodide extraction (Wako Chemicals USA).

Adaptor synthesis. The adaptors were synthesized from two oligos,designated as:

the primer strand: (SEQ ID NO: 1)AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGA CGCTCTTCCGATCT; andthe template strand: (SEQ ID NO: 2)/5phos/ACTGNNNNNNNNNNNNAGATCGGAAGAGCACACGTCTG AACTCCAGTCAC

The two adaptor strands were annealed by combining equimolar amounts ofeach oligo to a final concentration of 50 micromolar and heating to 95°C. for 5 minutes. The oligo mix was allowed to cool to room temperaturefor over 1 hour. The annealed primer-template complex was extended in areaction consisting of 40 micromolar primer-template, 25 units Klenowexo-DNA polymerase (New England Biolabs), 250 micromolar each dNTP, 50mM NaCl, 10 mM Tris-HCl pH 7.9, 10 mM MgCl₂, and 1 mM dithiothreitol(DTT) for 1 hour at 37° C. The product was isolated by ethanolprecipitation. Due to the partial A-tailing property of Klenow exo-,this protocol results in a mixture of blunt-ended adapters and adapterswith a single-nucleotide A hverhang. A single-nucleotide A overhang wasadded to residual blunt fragments by incubating the adapters with 25units Klenow exo-, 1 mM dATP, 50 mM NaCl, 10 mM Tris-HCl pH 7.9, 10 mMMgCl2, and 1 mM dithiothreitol (DTT) for 1 hour at 37° C. The productwas again ethanol precipitated and resuspended to a final concentrationof 50 micromolar.

Sequencing library preparation. 3 micrograms of DNA was diluted into 130microliters of TE buffer (10 mM tris-HCl, pH 8.0, 0.1 M EDTA) and wassheared on the Covaris AFA system with duty cycle 10%, intensity 5,cycles/burst 200, time 20 seconds×6, temperature 4° C. DNA was purifiedwith 2 volumes of Agencourt AMPure XP beads per the manufacturer'sprotocol. After end-repair with the NEB end-repair kit per themanufacturer's protocol, DNA fragments larger than the optimal range of−200-500 bp were removed by adding 0.7 volumes of AMPure XP beads andtransferring the supernatant to a separate tube (fragments larger than500 bp bind to the beads and are discarded). An additional 0.65 volumesof AMPure XP beads were added (this step allows fragments ofapproximately 200 bp or greater to bind to the beads). The beads werewashed and DNA eluted. DNA was then T-tailed in a reaction containing 5units Klenow exo-, 1 mM dTTP, 50 mM NaCl, 10 mM Tris-HCl pH 7.9, 10 mMMgCl2, 1 mM. The reaction proceeded for 1 hour at 37 C. DNA was purifiedwith 1.2 volumes of AMPure XP beads. The custom adaptors were ligated bycombining 750 ng of T-tailed DNA with 250 pmol adaptors in a reactioncontaining 3000 units T4 DNA ligase, 50 mM Tris-HCl pH 7.6, 10 mM MgCl2,5 mM DTT, 1 mM ATP. The reaction was incubated 25 C for 15 minutes, andpurified with 1.2 volumes of AMPure XP beads.

Pre-capture amplification. 375 ng adaptor-ligated DNA was PCR amplifiedwith primers AATGATACGGCGACCACCGAG (SEQ ID NO:3) andGTGACTGGAGTTCAGACGTGTGC (SEQ ID NO:4) using the Kappa high-fidelity PCRkit for 8 cycles with an annealing temperature of 60 C. The product waspurified with 1.2 volumes of AMPure XP beads.

DNA capture. Target capture was performed with the Agilent SureSelectsystem per the manufacturer's recommendations, except that capturevolumes were performed at one-half of the standard volume. The captureset targeted an arbitrary 758 kb region of the genome consisting of bothcoding and noncoding sequences. Capture baits were 120 nt in length, andwere prepared with the Agilent eArray tool with 3× tiling.

Post-capture amplification. Captured DNA was amplified with PCR primersAATGATACGGCGACCACCGAG (SEQ ID NO:3) and CAAGCAGAAGACGGCATACGAGATXXXXXXGTGACTGGAGTTCAGACGTGTGC (SEQ ID NO:5) whereXXXXXX indicates the position of a fixed multiplexing barcode sequence).2 0 fmol of DNA was used per lane for sequencing on an Illumina HiSeq2000.

Data processing. Reads with intact SMI adaptors include a 12 nucleotiderandom sequence, followed by a 5 nucleotide fixed sequence. These readswere identified by filtering out reads that lack the expected fixedsequence at positions 13-17. The SMI sequence from both the forward andreverse sequencing reads (i.e., the first and second degenerate n-mersequences) was computationally added to the read header, and the fixedsequence removed. The first 4 nucleotides located following the adaptorsequence were also removed due to the propensity for ligation andend-repair errors to result in an elevated error rate near the end ofthe DNA fragments. Reads having common (i.e., identical) SMI sequenceswere grouped together, and were collapsed to generate a consensus read.Sequencing positions were discounted if the consensus group coveringthat position consisted of fewer than 3 members, or if fewer than 90% ofthe sequences at that position in the consensus group had the identicalsequence. Reads were aligned to the human genome with theBurrows-Wheeler Aligner (BWA). The consensus sequences were then pairedwith their strand-mate by grouping each 24 nucleotide tag of form AB inread 1 with its corresponding tag of form BA in read 2. Resultantsequence positions were considered only when information from both DNAstrands was in perfect agreement. An overview of the data processingworkflow is as follows:

-   -   1. Discard reads that do not have the 5 nt fixed reference (or        “spacer”) sequence (CAGTA; SEQ ID NO:6) present after 12 random        nucleotides.    -   2. Combine the 12 nt SMI tags from read 1 and read 2, and        transfer the combined 24 nt SMI sequence into the read header.    -   3. Discard SMIs with inadequate complexity (i.e., those with >10        consecutive identical nucleotides).    -   4. Remove the 5 nt fixed reference sequence.    -   5. Trim an additional 4 nt from the 5′ ends of each read pair        (sites of error prone end repair).    -   6. Group together reads which have identical 24 nt SMIs.    -   7. Collapse to SMI consensus reads, scoring only positions with        3 or more SMI duplicates and >90% sequence identity among the        duplicates.    -   8. For each read in read 1 file having SMI of format AB, group        with corresponding DCS partner in read 2 with SMI of format BA.    -   9. Only score positions with identical sequence among both DCS        partners.    -   10. Align reads to the human genome.

Code for carrying out the workflow may be pre-existing or may involveprogramming within the skill of those in the art. In some embodiments,however, the Python code, which is illustrated in FIG. 10 , may be usedfor carrying out the pairing and scoring of partner strands according tosteps 8 and 9 of the workflow described above.

Overview

To overcome limitations in the sensitivity of variant detection bysingle-stranded next-generation DNA sequencing, an alternative approachto library preparation and analysis was designed, which is known hereinas Duplex Consensus Sequencing (DCS) (FIG. 1 ). The DCS method describedherein involves tagging both strands of duplex DNA with a random, yetcomplementary double-stranded nucleotide sequence, which is known hereinas a double-stranded single molecule identifier (SMI) sequence. The SMIsequences (in this case, double stranded SMI sequences) are incorporatedinto the SMI adaptor molecules by introducing a single-strandedrandomized nucleotide sequence into one adapter strand and the extendingthe opposite strand with a DNA polysmerase to yield a complementary,double-stranded SMI sequence (FIG. 2 ). The individually tagged strandsare then PCR amplified. Every duplicate that arises from a single strandof DNA will have the same SMI, and thus each strand in a DNA duplex pairgenerates a distinct, yet related population of PCR duplicates afteramplification owing to the complementary nature of the SMIs on the twostrands of the duplex. Comparing the sequence obtained from each of thetwo strands comprising a single molecule of duplex DNA facilitatesdifferentiation of sequencing errors from true mutations. When anapparent mutation is, due to a PCR or sequencing error, the substitutionwill only be seen on a single strand. In contrast, with a true DNAmutation, complementary substitutions will be present on both strands(see FIG. 4C).

Following tagging with a double-stranded SMI and PCR amplification, afamily of molecules is obtained that arose from a single DNA molecule;members of the same PCR “family” are then grouped together by virtue ofhaving a common (i.e., the same) SMI tag sequence. The sequences ofuniquely tagged PCR duplicates are subsequently compared in order tocreate a PCR consensus sequence. Only DNA positions that yield the sameDNA sequence in a specified proportion of the PCR duplicates in afamily, such as 90% of the duplicates in one embodiment, are used tocreate the PCR consensus sequence. This step filters out random errorsintroduced during sequencing or PCR to yield the PCR consensussequences, each of which derives from an individual molecule ofsingle-stranded DNA. This set of PCR consensus sequences are calledsingle strand consensus sequences (SSCSs).

Next, PCR consensus sequences arising from two complementary strands ofduplex DNA can be identified by virtue of the complementary SMIs (FIG. 3) to identify the “partner SMI.” Specifically, a 24-nucleotide SMIconsists of two 12-nucleotide sequences that can be designated XY. Foran SMI of form XY in read 1, the partner SMI will be of form YX in read2. An example to illustrate this point is given in FIG. 4 . Followingpartnering of two strands by virtue of their complementary SMIs, thesequences of the strands are compared. Sequence reads at a givenposition are kept only if the read data from each of the two pairedstrands is in agreement.

Results

In order to label or tag each of the strands of duplex DNA with uniquecomplementary tags, adaptors which contain the standard sequencesrequired for the Illumina HiSeq system were synthesized, but withaddition of a double-stranded, complementary SMI sequence (or “tag”) of12 random nucleotides (or a random “degenerate sequence”) per strand.Target DNA molecules having a random SMI sequence n-mer that is 12nucleotides in length on each end will therefore have a unique 24nucleotide SMI sequence. The adaptors were prepared (FIG. 2 ) from twopartially complementary oligonucleotides, one of which has asingle-stranded 12 nucleotide random nucleotide sequence (i.e. a firstrandom degenerate nucleotide n-mer sequence) followed by a singlestranded fixed reference sequence that is 4 nucleotides in length. Thesingle-stranded random nucleotide tag was converted to adouble-stranded, complementary SMI tag by extension with Klenow exo- DNApolymerase and the extended adaptor was purified by ethanolprecipitation. Due to the partial A-tailing property of Klenow exo-,this protocol results in a mixture of blunt-ended adaptors and adaptorswith a single-nucleotide A overhang (data not shown). Asingle-nucleotide A-overhang was added to the residual blunt fragmentsby incubating the adaptors with Klenow exo- DNA polymerase and a highconcentration of dATP (1 mM), and purified the adaptors again by ethanolprecipitation.

DNA for sequencing was sheared and end-repaired by standard methods,with size-selection for fragments in the range of ˜200-500 bp bysize-selective binding to Ampure XP beads. Standard Illumina librarypreparation protocols involve ligating A-tailed DNA to T-tailedadaptors. However, because A-tailed adaptors were used, the DNA wasT-tailed by incubating the end-repaired DNA with Klenow exo- DNApolymerase and 1 mM dTTP. The adaptor-ligated library was PCR amplifiedand subjected to SureSelect capture, with targeting of an arbitrary 758kb portion of the genome (DNA coordinates available upon request). Theefficiency of adaptor ligation, PCR amplification, DNA capture, andsequencing were comparable to those seen with standard librarypreparation methods (data not shown). Although Agilent Sure Selectprobes are used in this example, any suitable method of DNA selectionmay be used to capture particular target double-stranded DNA sequences.For example, selection and capture may be accomplished by any selectionby hybridization method (e.g., Agilent SureSelect, Primer ExtensionCapture, exploitation of biotinylated PCR amplicons as bait, AgilentHaloPlex) wherein probes that target the desired double-stranded DNAsequence may be recovered by an in-array capture (using probesimmobilized on glass slides) or by affinity using magnetic beads in anin-solution capture. In addition, mitochondrial and some other forms ofDNA may be isolated by size selection. Alternatively, in someembodiments, no enrichment is performed.

This protocol was used to sequence DNA isolated from normal colonicmucosa. Mutations were initially scored without consideration of the SMIsequences. PCR duplicates were filtered out with samtools rmdup, astandard tool which uses the shear points of DNA molecules to identifyPCR duplicates, as molecules arising from duplicated DNA will haveshared shear points. In order to focus specifically on non-clonalmutations, only those positions in the genome with at least 20× coverageand at which fewer than 5% of reads differed from the hg19 referencesequence were considered. This approach resulted in 70.9 millionnucleotides of sequence data and 56,890 mutations, indicating an overallmutation frequency of 8.03×10⁻⁴, in accord with the error rate ofIllumina next-generation sequencing of ˜0.1-1% [32].

Next, the SMI tags were used to group together PCR duplicates that arosefrom individual single-stranded DNA molecules and to create a consensussequence from the family of duplicates. At least 3 PCR duplicates wererequired, with at least 90% agreement in sequence among all duplicates,to consider a site for mutations. Scoring the mutation frequency asabove, again considering only sites with a minimum of 20× coverage andwith <5% of reads differing from reference, resulted in 145 millionnucleotides of sequence with 6,508 mutations and an overall mutationfrequency of 4.47×10⁻⁵, consistent with prior reports [36]. Notably, farmore nucleotides of DNA sequence were obtained in this approach (145million) than in the standard Illumina sequencing approach (70 million)detailed above which is dependent on use of the shear points ofsingle-ended reads to identify PCR duplicates. The improved sequencecoverage arose from use of the SMI to identify PCR duplicates, becauseidentifying PCR duplicates by consideration of uniquely sheared DNA endsis fundamentally limited by the small number of possible shear pointsthat overlap a given position of the genome and the propensity forspecific genomic regions to be more readily undergo shearing. Thusfiltering PCR duplicates by using shear points resulted in discarding alarge portion of the reads.

Finally, the complementary nature of the double-stranded SMI sequenceswas used to identify pairs of consensus groups that arose fromcomplementary DNA strands. Sequence reads were considered only when theread data from each of the two strands is in perfect agreement. In apilot experiment, after grouping of PCR duplicates as above, 29,409 SMIpartner pairs were found, indicative that fewer than 1% of tags hadtheir corresponding partner tag present in the library. The low recoveryof tag pairs was most likely due to inadequate amplification of thestarting DNA library. Among these tag-pairs, 24,772 duplex consensusstrands were identified with an average strand length of 82 nucleotides,resulting in 2 million nucleotides of DNA consensus sequence. Thesequences of the paired duplex strands disagreed at 3,585 of thenucleotide positions, indicative of single-stranded errors (i.e. PCR orsequencing errors); these sites of disagreement were removed, leavingonly bases at which the sequence of both duplex strands were in perfectagreement. Next, as above, analysis of mutation frequencies wasrestricted to sites with at least 10× coverage and at which fewer than10% of reads disagreed from the hg19 reference sequence. Because the 2million nucleotides of read data were spread across a 758 kb target, ouraverage depth was only ˜3×. Thus only 14,464 nucleotides of DNA sequencecorresponded to sites with at least 10× depth. Among these sites, zeromutations were seen. To increase the number of tag pairs considered,analysis described above was repeated, but PCR duplicates were groupedwith a minimum of only 1 duplicate per site. This resulted in 28,359nucleotides of DNA sequence with at least 10× depth. Again, no mutationswere detected.

Current experiments are being performed on vastly smaller target DNAmolecules (ranging from ˜300 bp to ˜20 kb in size). Use of smaller DNAtargets will allow for much greater sequencing depth, and far moreaccurate assessment of the background mutation rate of the assay. Inaddition, the protocol has been modified to incorporate a greater numberof PCR cycles initiated off a smaller number of genome equivalents,which will increase the fraction of tags for which both of the partnertag strands have been sufficiently amplified to be represented in thefinal sequence data. Indeed, among the 3.6 million SMIs present in ourinitial library which underwent PCR duplication, 1.5 million of the SMIswere present only once, indicating insufficient amplification of the DNAdue in part to the low number of PCR cycles used.

Example 2: Duplex Sequencing of Human Mitochondrial DNA

Materials and Methods

In addition to those described in Example 1 above, the followingmaterials and methods were also used.

DNA Isolation. Mitochondrial DNA was isolated as previously described(4).

Data processing. The entire human genome sequence (hg19) was used asreference for the mitochondrial DNA experiment, and reads that mapped tochromosomal DNA were removed. Reads sharing identical tag sequences werethen grouped together and collapsed to consensus reads. Sequencingpositions were discounted if the consensus group covering that positionconsisted of fewer than three members or if fewer than 90% of thesequences at that position in the consensus group had the identicalsequence. A minimum group size of three was selected becausenext-generation sequencing systems have an average base calling errorrate of ˜1/100. Requiring the same base to be identified in threedistinct reads decreases the frequency of single-strand consensussequence (SSCS) errors arising from base-call errors to (1/100)3=1×10⁻⁶,which is below the frequency of spontaneous PCR errors thatfundamentally limit the sensitivity of SSCSs. The requirement for 90% ofsequences to agree to score a position is a highly conservative cutoff.For example, with a group size of eight, a single disagreeing read willlead to 87.5% agreement and the position will not be scored. If allgroups in an experiment are of size nine or less, this cutoff will thusrequire perfect agreement at any given position to score the position.Further development of our protocol may allow for less stringentparameters to be used to maximize the number of SSCS and duplexconsensus sequence (DCS) reads that can be obtained from a givenexperiment.

Results

Having established the methodology for Duplex Sequencing with M13mp2DNA, which is a substrate for which the mutation frequency and spectrumare fairly well established, it was desired to apply the approach to ahuman DNA sample. Thus, mitochondrial DNA was isolated from human braintissue and sequenced the DNA after ligation of Duplex Sequencingadapters. A standard sequencing approach with quality filtering for aPhred score of 30 resulted in a mutation frequency of 2.7×10-3, and SSCSanalysis yielded a mutation frequency of 1.5×10-4. In contrast, DCSanalysis revealed a much lower overall mutation frequency of 3.5×10-5(FIG. 5A). The frequency of mutations in mitochondrial DNA haspreviously been difficult to measure directly due in part to sources oferror in existing assays that can result in either overestimation orunderestimation of the true value. An additional confounder has beenthat most approaches are limited to interrogation of mutations within asmall fraction of the genome [56]. The method of single-molecule PCR,which has been proposed as an accurate method of measuring mitochondrialmutation frequency and is considered resistant to damage-inducedbackground errors [57], has resulted in a reported mitochondrialmutation frequency in human colonic mucosa of 5.9×10-5±3.2×10-5 [56],which is in excellent agreement with our result. Likewise, mitochondrialDNA sequence divergence rates in human pedigrees are consistent with amitochondrial mutation frequency of 3-5×10-5 [58, 59].

When the distribution of mutations throughout the mitochondrial genomeis considered, the quality filtered reads (analyzed withoutconsideration of the tags) have many artifactual errors, such thatidentification of mutational hotspots is difficult or impossible (FIG.5B). DCS analysis removed these artifacts (FIG. 5C) and revealedstriking hypermutability of the region of replication initiation (Dloop), which is consistent with prior estimates of mutational patternsin mitochondrial DNA based upon sequence variation at this region withinthe population [60].

SSCS analysis produced a strong mutational bias, with a 130-fold excessof G→*T relative to C→*A mutations (FIG. 5D), consistent with oxidativedamage of the DNA leading to first-round PCR mutations as a significantsource of background error. A high level of oxidative damage is expectedin mitochondrial DNA, due to extensive exposure of mitochondria to freeradical species generated as a byproduct of metabolism [61]. DCSanalysis (FIG. 5E) removed the mutational bias and revealed thattransition mutations are the predominant replication errors inmitochondrial DNA. The DCS mutation spectrum is in accord with priorestimates of deamination events and T-dGTP mispairing by themitochondrial DNA polymerase as primary mutational forces inmitochondrial DNA. Furthermore, the mutation spectrum of ourmitochondrial data are consistent with previous reports of heteroplasmicmutations in human brain showing an increased load of A→G/T→C andG→A/C→J transitions, relative to transversions [64, 65]. A similarspectral bias has also been reported in mice [62, 66] and in populationstudies of Drosophila melanogaster [67].

Example 3: Demonstration of Error-Correction by DCS Using RandomlySheared DNA Ends as Single Molecule Identifiers

Materials and Methods

In addition to those described in the Examples above, the followingmaterials and methods were also used to demonstrate the capability ofDCS analysis to remove sequencing errors

Sequencing library preparation. Genomic DNA was isolated from aderivative of Saccharomyces cerevisiae strain SC288 by standard methods.The DNA was randomly sheared by the Covaris AFA system, followed byend-repair, A-tailing, and ligation of Illumina TruSeq DNA sequencingadaptors, all by standard library preparation methods. The resultantsequence data consisted of an average 32.5 fold depth of the 12 megabaseS. cerevisiae genome.

Data analysis. The first 10 nucleotides of each sequencing read pair,corresponding to the randomly sheared DNA ends, were combined, such thatthe first 10 nucleotides of read 1, referred to as A, was combined withthe first 10 nucleotides of read 2, referred to as B, to yield an SMItag of form AB. Reads were grouped according to SMI sequence, andnucleotide reads were considered only if they agreed among at least 90%of family members sharing a given tag sequence. For DCS analysis, a tagof form AB1 is partnered with the corresponding tag of form BA2, andnucleotide positions are considered only when the sequence is inagreement among read pairs with matching tags AB1 and BA2.

Results

In order to demonstrate the capability of DCS analysis to removesequencing errors, a sequencing library was prepared under standardconditions with commercially available sequencing adaptors, and therandomly sheared DNA ends were used as SMI's. First, reads were groupedby SMI with a minimum family size of 1 member. Considering only siteswith a minimum of 20× coverage and with <5% of reads differing fromreference, this analysis resulted in 644.8 million nucleotides ofsequence data and 2,381,428 mutations, yielding an overall mutationfrequency of 3.69×10⁻³.

The data was then subjected to DCS analysis with the SMI tags, searchingfor tags of form AB1 that have partner tags of form BA2, and consideredonly positions at which the sequence from the two strands was in perfectagreement. 3.1% of the tags had a matching partner present in thelibrary, resulting in 2.9 million nucleotides of sequence data. Thesequences of the duplex strands were not complementary at 40,874nucleotide positions; these disagreeing positions, representing likelysequencing or PCR errors, were removed from analysis. Again consideringpositions with at least 20× coverage and <5% of reads differing fromreference, 3.0 million nucleotides of sequence data and 157 mutationswere obtained, with an overall mutation frequency of 5.33×10⁻⁵,indicative of removal of >98% of mutations seen in raw analysis andthereby demonstrating the capability of DCS to lower the error rate ofDNA sequencing.

To compare this result to the method of Kinde et al. [36], reads weregrouped into families by SMI tag as before but filtered for familieswith a minimum of 3 members. This resulted in 1.4 million nucleotides ofsequence data and 61 mutations, with an overall mutation frequency of4.25×10⁻⁵. Thus, the method of Kinde et al., with a minimum family sizeof 3, resulted in less than half as much resultant sequence data afterfiltering than was obtained by DCS with a minimum family size of 1.Thus, DCS lowered the error rate of sequencing to a comparable degree toa method considered state-of-the-art, but with less loss of sequencingcapacity.

Discussion

It was demonstrated that DCS analysis, using sheared DNA ends as uniquemolecular identifiers, results in a lowering of the apparent error rateof DNA sequencing. As this proof-of-concept experiment was performed ona library that was not optimized to maximize recovery of both strands,there were not sufficient strand-pairs recovered to perform DCS analysiswith a minimum family size of >1 member. Requiring family sizes >1 isexpected to further reduce sequencing errors. Moreover, this analysiswas limited in that it did not include ligation of degenerate SMI tagsequences; owing to the limited number of shear points flanking anygiven nucleotide position, use of shear points as SMIs limits the numberof unique molecules that can be sequenced in a single experiment. Theuse of shear points as SMIs in conjunction with an exogenously ligatedSMI tag sequence would allow for increased depth of sequencing at anygiven nucleotide position.

Example 4: Demonstrations of Duplex Consensus Sequencing

In addition to those described in Examples 1 and 2 above, the followingmaterials and methods were also used.

Materials and Methods

Construction of M13mp2 Variants. M13mp2 gapped DNA encoding the LacZ afragment was extended by human DNA polymerase δ [2] and the resultantproducts were transformed into Escherichia coli and subjected toblue-white color screening as previously described [3]. Mutant plaqueswere sequenced to determine the location of the mutation resulting inthe color phenotype. A series of mutants, each differing from wild typeby a single nucleotide change, were then mixed together with wild-typeM13mp2 DNA to result in a single final mixture with distinct mutantsrepresented at ratios of 1/10 (G6267A), 1/100 (T6299C), 1/1,000(G6343A), and 1/10,000 (A6293T).

Oxidative Damage of M13mp2 DNA. Induction of DNA damage was performed byminor modifications to a published protocol [5]: 300 ng of M13mp2double-stranded DNA was incubated in 10 mM sodium phosphate buffer, pH7.0, in the presence of 10 μM iron sulfate and 10 μM freshly dilutedhydrogen peroxide. Incubation proceeded for 30 min at 37° C. in open1.5-mL plastic microcentrifuge tubes.

DNA Isolation. M13mp2 DNA was isolated from E. coli strain MC1061 byQiagen Miniprep. To allow for greater sequencing depth at a definedregion of the M13mp2 genome, an 840-bp fragment was enriched by completedigestion with the restriction enzymes Bsu36l and Nael (New EnglandBiolabs), followed by isolation of the fragment on an agarose gel by theRecochip system (Takara Bio).

Duplex Consensus Sequencing of M13 DNA Removes Artifactual SequencingErrors.

The spontaneous mutation rate of M13mp2 DNA has been well established bya number of exquisitely sensitive genetic assays to be 3.0E-6 [53], thatis, an average of one spontaneous base substitution error for every330,000 nucleotides. Thus this substrate is well suited as a control fordetermining the background error frequency of DNA sequencing. M13mp2 DNAwas sheared and ligated to adaptors containing double-strandedcomplementary SMI sequences by standard protocols, and was subjected todeep sequencing on an Illumina HiSeq 2000 followed by ConsensusSequencing analysis (FIG. 6 ).

Analysis of the data by standard methods (i.e., without consideration ofthe double stranded SMI sequences) resulted in an error frequency of3.8E-03, more than one thousand fold higher than the true mutationfrequency of M13mp2 DNA. This indicates that >99.9% of the apparentmutations identified by standard sequencing are in fact artifactualerrors.

The data were then analyzed by Single Strand Consensus Sequencing(SSCS), using the unique SMI tag affixed to each molecule to group PCRproducts together in order to create a consensus of all PCR productsthat came from an individual molecule of single-stranded DNA. Thisresulted in a mutation frequency of 6.4E-OS, suggesting that −98% ofsequencing errors are corrected by SSCS.

Next, the data were subjected to Duplex Consensus Sequencing (DCS),which further corrects errors by using the complementary SMI tags tocompare the DNA sequence arising from both of the two strands of asingle molecule of duplex DNA. This approach resulted in a mutationfrequency of 2.SE-06, in nearly perfect agreement with the true mutationfrequency of M13mp2 DNA of 3.0E-06. The number of nucleotides of DNAsequence obtained by a standard sequencing approach, and after SSCS andDCS analysis, may be found in Table 1 below.

TABLE 1 Data yield from Duplex Sequencing M13mp2 DNA Mitochondrial DNAInitial nucleotides 6.5 × 10⁹ 6.2 × 10⁹ SSCS nucleotides 8.7 × 10⁷ 4.1 ×10⁸ DCS nucleotides 2.2E × 10⁷   9.7 × 10⁷ Initial reads per SSCS read 75 15 Initial reads per DCS read 295 64 SSCS reads per DCS read  4 4

-   -   Initial nucleotides represent raw reads that contain the        expected fixed adapter sequence following 12 degenerate        nucleotides and map to the reference genome. Apparent nucleotide        loss in converting initial reads to SSCSs occurs because many of        the initial reads intentionally represent identical PCR        duplicates of single-stranded DNA molecules to allow for removal        of sequencing and PCR errors by comparison of the sequence among        the duplicates. A minimum of three initial reads are required to        produce one SSCS; however, a greater average number is necessary        to ensure that most DNA fragments have at least this number of        duplicates. Under fully optimized conditions, each DCS read        would arise from exactly two SSCS reads (one arising from each        strand of the initial molecule of duplex DNA). An SSCS:DCS ratio        greater than 2 indicates that the strand partner of some SSCSs        was not recovered.

For an artifactual error to be scored by DCS, complementary artifactualerrors must occur on both strands of a molecule of duplex DNA. Thus thebackground (artifactual) error frequency of DCS may be calculated as:(probability of error on one strand)*(probability of error on otherstrand)*(probability that both errors are complementary).

As the background error frequency of SSCS in this experiment was −6E-S,the background error frequency of DCS can be calculated as6E-S*6E-S*(1/3)=1.2E-9. This represents a greater than 3 million foldimprovement over the error rate of 3.SE-03 that was obtained by astandard sequencing approach.

Consensus Sequencing Reveals Likely Sites of DNA Damage

M13mp2 DNA was sequenced as detailed above, with DCS adaptors containingdouble-stranded complementary SMIs. The spectrum of mutations obtainedwith SSCS was determined. Data was filtered to consist offorward-mapping reads from Read 1, i.e. sequencing of the referencestrand, and reverse-mapping reads from Read 1, i.e. sequencing of theanti-reference strand. True mutations would result in an equal balancebetween mutations on the reference strand and their complementarymutation on the anti-reference strand.

However, SSCS analysis revealed a large number of single-stranded GTmutations on reads mapping in the forward orientation to the referencegenome, with a much smaller number of CA mutations mapping to thereverse orientation. The spectrum of mutations identified by both SSCSand DCS analysis were examined relative to literature reference valuesfor the M13mp2 substrate (FIG. 7A). SSCS analysis revealed a largeexcess of G→A/C→J and G→T/C→A mutations relative to reference (P <10-6,two-sample t test). In contrast, DCS analysis was in excellent agreementwith the literature values with the exception of a decrease relative toreference of these same mutational events: G→A/C→J and G→T/C→A (P<0.01).To probe the potential cause of these spectrum deviations, the SSCS datawere filtered to consist of forward-mapping reads from read 1 (i.e.,direct sequencing of the reference strand) and the reverse complement ofreverse-mapping reads from read 1 (i.e., direct sequencing of theantireference strand.) True double-stranded mutations should result inan equal balance of complementary mutations observed on the referenceand antireference strand. However, SSCS analysis revealed a large numberof single-stranded G→T mutations, with a much smaller number of C→Amutations (FIG. 7B). A similar bias was seen with a large excess of C→Jmutations relative to G→A mutations.

Base-specific mutagenic DNA damage is a likely explanation of theseimbalances. Excess G→T mutations are consistent with the oxidativeproduct 8-oxo-guanine (8-oxo-G) causing first round PCR errors andartifactual G→T mutations. DNA polymerases, including those commonlyused in PCR, have a strong tendency to insert adenine opposite 8-oxo-G[45, 54], and misinsertion of A opposite 8-oxo-G would result inerroneous scoring of a G→T mutation. Likewise, the excess C→J mutationsare consistent with spontaneous deamination of cytosine to uracil [47],a particularly common DNA damage event that results in insertion duringPCR of adenine opposite uracil and erroneous scoring of a C→J mutation.

To determine whether the excess G→T mutations seen in SSCSs mightreflect oxidative DNA damage at guanine nucleotides, before sequencinglibrary preparation M13mp2 DNA was incubated with the free radicalgenerator hydrogen peroxide in the presence of iron, a protocol thatinduces DNA damage [55]. This treatment resulted in a substantialfurther increase in G→T mutations by SSCS analysis (FIG. 8A), consistentwith PCR errors at sites of DNA damage as the likely mechanism of thisbiased mutation spectrum. In contrast, induction of oxidative damage didnot alter the mutation spectrum seen with DCS analysis (FIG. 8B),indicating that duplex consensus sequences are not similarly susceptibleto DNA damage artifacts.

Furthermore, relative to the literature reference values, DCS analysisresults in a lower frequency of G→T/C→A and C→T/G→A mutations (FIG. 7A),which are the same mutations elevated in SSCS analysis as a probableresult of DNA damage. Notably, the M13mp2 LacZ assay, from whichreference values have been derived, is dependent upon bacterialreplication of a single molecule of M13mp2 DNA. Thus, the presence ofoxidative damage within this substrate could cause an analogousfirst-round replication error by Escherichia coli, converting asingle-stranded damage event into a fixed, double-stranded mutationduring replication. The slight reduction in the frequency of these twotypes of mutations measured by DCS analysis may, therefore, reflect theabsence of damage-induced errors that are scored by the in vivo LacZassay.

Consensus Sequencing Accurately Recovers Spiked-In Control Mutations.

A series of M13mp2 variants were constructed which contain known singlebase substitutions. These variants were then mixed together at knownratios, and the mixture was prepared for sequencing with DCS adaptorswith double-stranded complementary SMIs and was sequenced on an IlluminaHiSeq 2000. The data was then analyzed by consensus sequencing (FIG. 9). With conventional analysis of the data (i.e. without consideration ofthe SMI tags), variants present at a level of <1/100 could not beaccurately identified. This limitation occurs because at any givenposition, artifactual mutations are seen at a level of nearly 1/100.

In contrast, when the data is analyzed by Single Strand ConsensusSequencing (SSCS) with −20,000 fold depth, accurate recovery of mutantsequence is seen down to one mutant molecule per 10,000 wild typemolecules. Duplex Consensus Sequencing (DCS), which was not performed onthis sample, would allow for detection of even rarer mutations.

REFERENCES

The references, patents and published patent applications listed below,and all references cited in the specification above are herebyincorporated by reference in their entirety, as if fully set forthherein.

-   [1] Metzker M L. Sequencing technologies—the next generation. Nat    Rev Genet. 2010; 11:31-46.-   [2] Shendure J, Ji H. Next-generation DNA sequencing. Nat    Biotechnol. 2008; 26:1135-45.-   [3] Lecroq B, Lejzerowicz F, Bachar D, Christen R, Esling P,    Baerlocher L, et al. Ultra-deep sequencing of foraminiferal    microbarcodes unveils hidden richness of early monothalamous    lineages in deep-sea sediments. Proc Natl Acad Sci USA. 2011;    108:13177-82.-   [4] Mackelprang R, Waldrop M P, DeAngelis K M, David M M, Chavarria    K L, Blazewicz S J, et al. Metagenomic analysis of a permafrost    microbial community reveals a rapid response to thaw. Nature. 2011;    480:368-71.-   [5] Garćia-GarceràM, Gigli E, Sanchez-Quinto F, Ramirez O, Calafell    F, Civit S, et al. Fragmentation of contaminant and endogenous DNA    in ancient samples determined by shotgun sequencing; prospects for    human palaeogenomics. PLoS ONE. 2011; 6:e24161.-   [6] Fordyce S L, Ávila-Arcos M C, Rockenbauer E, Borsting C,    Frank-Hansen R, Petersen F T, et al. High-throughput sequencing of    core STR loci for forensic genetic investigations using the Roche    Genome Sequencer FLX platform. BioTechniques. 2011; 51:127-33.-   [7] Druley T E, Vallania F L M, Wegner D J, Varley K E, Knowles O L,    Bonds J A, et al. Quantification of rare allelic variants from    pooled genomic DNA. Nat Methods. 2009; 6:263-5.-   [8] Out A A, van Minderhout IJHM, Goeman J J, Ariyurek Y, Ossowski    S, Schneeberger K, et al. Deep sequencing to reveal new variants in    pooled DNA samples. Hum Mutat. 2009; 30:1703-12.-   [9] Fan H C, Blumenfeld Y J, Chitkara U, Hudgins L, Quake S R.    Noninvasive diagnosis of fetal aneuploidy by shotgun sequencing DNA    from maternal blood. Proc Natl Acad Sci USA. 2008; 105:16266-71.-   [10] Chiu R W K, Akolekar R, Zheng Y W L, Leung T Y, Sun H, Chan K C    A, et al. Non-invasive prenatal assessment of trisomy 21 by    multiplexed maternal plasma DNA sequencing: large scale validity    study. BMJ. 2011; 342:c7401.-   [11] Mitchell P S, Parkin R K, Kroh E M, Fritz B R, Wyman S K,    Pogosova-Agadjanyan E L, et al. Circulating microRNAs as stable    blood-based markers for cancer detection. Proc Natl Acad Sci USA.    2008; 105:10513-8.-   [12] Ding L, Ley T J, Larson D E, Miller C A, Koboldt D C, Welch J    S, et al. Clonal evolution in relapsed acute myeloid leukaemia    revealed by whole-genome sequencing. Nature. 2105; 481:506-9.-   [13] Boyd S D, Marshall E L, Merker J D, Maniar J M, Zhang L N,    Sahaf B, et al. Measurement and Clinical Monitoring of Human    Lymphocyte Clonality by Massively Parallel V-D-J Pyrosequencing.    Science Translational Medicine. 2009; 1:12ra23-12ra23.-   [14] Hyman R W, Herndon C N, Jiang H, Palm C, Fukushima M, Bernstein    D, et al. The dynamics of the vaginal microbiome during infertility    therapy with in vitro fertilization-embryo transfer. J Assist Reprod    Genet. 2012; 29:105-15.-   [15] LaTuga M S, Ellis J C, Cotton C M, Goldberg R N, Wynn J L,    Jackson R B, et al. Beyond bacteria: a study of the enteric    microbial consortium in extremely low birth weight infants. PLoS    ONE. 2011; 6:e27858.-   [16] Minot S, Sinha R, Chen J, Li H, Keilbaugh S A, Wu G D, et al.    The human gut virome: interindividual variation and dynamic response    to diet. Genome Res. 2011; 21:1616-25.-   [17] Yang J, Yang F, Ren L, Xiong Z, Wu Z, Dong J, et al. Unbiased    parallel detection of viral pathogens in clinical samples by use of    a metagenomic approach. J Clin Microbiol. 2011; 49:3463-9.-   [18] Nasu A, Marusawa H, Ueda Y, Nishijima N, Takahashi K, Osaki Y,    et al. Genetic heterogeneity of hepatitis C virus in association    with antiviral therapy determined by ultra-deep sequencing. PLoS    ONE. 2011; 6:e24907.-   [19] Campbell P J, Pleasance E D, Stephens P J, Dicks E, Rance R,    Goodhead I, et al. Subclonal phylogenetic structures in cancer    revealed by ultra-deep sequencing. Proc Natl Acad Sci USA. 2008;    105:13081-6.-   [20] De Grassi A, Segala C, lannelli F, Volorio S, Bertario L,    Radice P, et al. Ultradeep Sequencing of a Human Ultraconserved    Region Reveals Somatic and Constitutional Genomic Instability. PLoS    Biol. 2010; 8:e1000275.-   [21] Zagordi O, Klein R, Däumer M, Beerenwinkel N. Error correction    of next-generation sequencing data and reliable estimation of HIV    quasispecies. Nucleic Acids Research. 2010; 38:7400-9.-   [22] Wang C, Mitsuya Y, Gharizadeh B, Ronaghi M, Shafer R W.    Characterization of mutation spectra with ultra-deep pyrosequencing:    application to HIV-1 drug resistance. Genome Res. 2007; 17:1195-201.-   [23] Carlson C A, Kas A, Kirkwood R, Hays L E, Preston B D,    Salipante S J, et al. Decoding cell lineage from acquired mutations    using arbitrary deep sequencing. Nat Methods. 2012; 9:78-80.-   [24] He Y, Wu J, Dressman D C, lacobuzio-Donahue C, Markowitz S D,    Velculescu V E, et al. Heteroplasmic mitochondrial DNA mutations in    normal and tumour cells. Nature. 2010; 464:610-4.-   [25] Ameur A, Stewart J B, Freyer C, Hagström E, Ingman M, Larsson    N-G, et al. Ultra-Deep Sequencing of Mouse Mitochondrial DNA:    Mutational Patterns and Their Origins. PLoS Genet. 2011; 7:e1002028.-   [26] Kanagawa T. Bias and artifacts in multitemplate polymerase    chain reactions (PCR). J Biosci Bioeng. 2003; 96:317-23.-   [27] Meyerhans A, Vartanian J P, Wain-Hobson S. DNA recombination    during PCR. Nucleic Acids Research. 1990; 18:1687-91.-   [28] Quail M A, Kozarewa I, Smith F, Scally A, Stephens P J, Durbin    R, et al. A large genome center's improvements to the Illumina    sequencing system. Nat Methods. 2008; 5:1005-10.-   [29] Salk J, Fox E, Loeb L. Mutational heterogeneity in human    cancers: origin and consequences. Annual Review of Pathology. 2009;    5:51-75.-   [30] Kozarewa I, Ning Z, Quail M A, Sanders M J, Berriman M, Turner    D J. Amplification-free Illumina sequencing-library preparation    facilitates improved mapping and assembly of (G+C)-biased genomes.    Nat Methods. 2009; 6:291-5.-   [31] Vandenbroucke I, Van Marck H, Verhasselt P, Thys K, Mostmans W,    Dumont S, et al. Minor variant detection in amplicons using 454    massive parallel pyrosequencing: experiences and considerations for    successful applications. BioTechniques. 2011; 51:167-77.-   [32] Flaherty P, Natsoulis G, Muralidharan O, Winters M, Buenrostro    J, Bell J, et al. Ultrasensitive detection of rare mutations using    next-generation targeted resequencing. Nucleic Acids Research. 2012;    40:e2-e.-   [33] Shen Y, Wan Z, Coarfa C, Drabek R, Chen L, Ostrowski E A, et    al. A SNP discovery method to assess variant allele probability from    next-generation resequencing data. Genome Res. 2010; 20:273-80.-   [34] Miner B E, Stöger R J, Burden A F, Laird C D, Hansen R S.    Molecular barcodes detect redundancy and contamination in    hairpin-bisulfite PCR. Nucleic Acids Research. 2004; 32:e135.-   [35] McCloskey M L, Stöger R, Hansen R S, Laird C D. Encoding PCR    products with batch-stamps and barcodes. Biochem Genet. 2007;    45:761-7.-   [36] Kinde I, Wu J, Papadopoulos N, Kinzler K W, Vogelstein B.    Detection and quantification of rare mutations with massively    parallel sequencing. Proc Natl Acad Sci USA. 2011; 108:9530-5. [37]    Jabara C B, Jones C D, Roach J, Anderson J A, Swanstrom R. Accurate    sampling and deep sequencing of the HIV-1 protease gene using a    Primer I D. Proc Natl Acad Sci USA. 2011; 108:20166-71.-   [38] Kivioja T, VAhirautio A, Karlsson K, Bonke M, Enge M,    Linnarsson S, et al. Counting absolute numbers of molecules using    unique molecular identifiers. Nat Methods. 2011; 9:72-4.-   [39] Casbon J A, Osborne R J, Brenner S, Lichtenstein C P. A method    for counting PCR template molecules with application to    next-generation sequencing. Nucleic Acids Research. 2011; 39:e81-e.-   [40] Shiroguchi K, Jia T Z, Sims P A, Xie X S. Digital RNA    sequencing minimizes sequence-dependent bias and amplification noise    with optimized single-molecule barcodes. Proc Natl Acad Sci USA.    2012; 109:1347-52.-   [41] Fu G K, Hu J, Wang P-H, Fodor S P A. Counting individual DNA    molecules by the stochastic attachment of diverse labels. Proc Natl    Acad Sci USA. 2011; 108:9026-31.-   [42] Cervantes R B, Stringer J R, Shao C, Tischfield J A, Stambrook    P J. Embryonic stem cells and somatic cells differ in mutation    frequency and type. Proc Natl Acad Sci USA. 2002; 99:3586-90.-   [43] Lindahl T, Wood R D. Quality control by DNA repair. Science.    1999; 286:1897-1905.-   [44] Kunkel, T A. Mutational specificity of depurination. Proc Natl    Acad Sci USA. 1984; 81:1494-98.-   [45] Shibutani S, Takeshita M, Grollman A P. Insertion of specific    bases during DNA synthesis past the oxidation-damaged base 8-oxodG.    Nature. 1991; 349:431-4.-   [46] Stiller M, Green R E, Ronan M, Simons J F, Du L, He W., et al.    Patterns of nucleotide misincorporations during enzymatic    amplification and direct large-scale sequencing of ancient DNA. Proc    Natl Acad Sci USA. 2006; 103:13578-84.-   [47] Ehrich M, Deciu C, Zwiefelhofer T, Tynan J A, Cagasan L, Tim R,    et al. Noninvasive detection of fetal trisomy 21 by sequencing of    DNA in maternal blood: a study in a clinical setting. Am J Obsbet    Gynecol. 2011; 204:205e1-11.-   [48] Bainbridge M N, Wang M, Burgess D L, Kovar C, Rodesch M,    D′Ascenzo M, et al. Whole exome capture in solution with 3 Gbp of    data. Genome Biol. 2010; 11::R62:1-8.-   [49] Travers K J, Chin C S, Rank D R, Eid J S, Turner S W. A    flexible and efficient template format for circular consensus    sequencing and SNP detection. Nucleic Acids Res. 2010; 38:159e1-8.-   [50] Kaur M, Makrigiorgos G M. Novel amplification of DNA in a    hairpin structure: towards a radical elimination of PCR errors from    amplified DNA. Nucleic Acids Res. 2003; 31:26e1-7.-   [51] Ozsolak, F., Platt, A. R., Jones, D. R., Reifenberger, J. G.,    Sass, L. E., McInerney, P., Thompson, J. F., Bowers, J., Jarosz, M.,    and Milos, P. M. (2009). Direct RNA sequencing. Nature 461, 814-818.-   [52] Lynch A M, Sasaki jC, Elespuru R, Jacobson-Kram D, Thybaud V,    et al. New and emerging technologies for genetic toxicity testing.    Environ Mol Mutagen. 2011; 52(3):205-23.-   [53] Thomas D C, Roberts J D, Sabatino R D, Myers T W, et al.    Fidelity of mammalian DNA replication and replicative DNA    polymerases. Biochemistry. 1991; 30:11751-9.-   [54] Kasai H, et al.(1993) Formation, inhibition of formation, and    repair of oxidative 8-hydroxyguanine DNA damage. Basic Life Sci    61:257-262.-   [55] McBride T J, Preston B D, Loeb L A (1991) Mutagenic spectrum    resulting from DNA damage by oxygen radicals. Biochemistry    30:207-213.-   [56] Greaves L C, et al. (2009) Quantification of mitochondrial DNA    mutation load. Aging Cell 8:566-572.-   [57] Kraytsberg Y, Nicholas A, Caro P, Khrapko K (2008) Single    molecule PCR in mtDNA mutational analysis: Genuine mutations vs.    damage bypass-derived artifacts. Methods 46:269-273.-   [58] Howell N, Kubacka I, Mackey D A (1996) How rapidly does the    human mitochondrial genome evolve? Am J Hum Genet 59:501-509.-   [59] Parsons T J, et al. (1997) A high observed substitution rate in    the human mitochondrial DNA control region. Nat Genet 15:363-368.-   [60] Stoneking M (2000) Hypervariable sites in the mtDNA control    region are mutational hotspots. Am J Hum Genet 67:1029-1032.-   [61] Kennedy S R, Loeb L A, Herr A J (2011) Somatic mutations in    aging, cancer and neurodegeneration. Mech Ageing Dev.-   [62] Vermulst M, et al. (2007) Mitochondrial point mutations do not    limit the natural lifespan of mice. Nat Genet 39:540-543.-   [63] Song S, et al. (2005) DNA precursor asymmetries in mammalian    tissue mitochondria and possible contribution to mutagenesis through    reduced replication fidelity. Proc Natl Acad Sci USA 102:4990-4995.-   [64] Lin M T, Simon D K, Ahn C H, Kim L M, Beal M F (2002) High    aggregate burden of somatic mtDNA point mutations in aging and    Alzheimer's disease brain. Hum Mol Genet 11:133-145.-   [65] Jazin E E, Cavelier L, Eriksson I, Oreland L, Gyllensten    U (1996) Human brain contains high levels of heteroplasmy in the    noncoding regions of mitochondrial DNA. Proc Natl Acad Sci USA    93:12382-12387.-   [66] Khaidakov M, Heflich R H, Manjanatha M G, Myers M B, Aidoo    A (2003) Accumulation of point mutations in mitochondrial DNA of    aging mice. Mutat Res 526:1-7.-   [67] Haag-Liautard C, et al. (2008) Direct estimation of the    mitochondrial DNA mutation rate in Drosophila melanogaster. PLoS    Biol 6:e204.

1-20. (canceled)
 21. A method of sequencing double-stranded cell-freeDNA (cfDNA) molecules, the method comprising: (a) ligating partiallydouble-stranded adapters to both ends of the double-stranded cfDNAmolecules to form adapter-target complexes, wherein (i) thedouble-stranded adapters each comprise an identifier sequence, (ii) atleast two adapters comprise the same identifier sequence and are ligatedto different cfDNA molecules, and (iii) cfDNA end sequences togetherwith associated identifier sequences form tags at both ends of the cfDNAmolecules; and (iv) individual adapter-target complexes comprisedifferent pairs of tags; (b) amplifying the adapter-target complexes toproduce a plurality of adapter-target amplification products from eachof a first strand and a complementary second strand of theadapter-target complexes; (c) sequencing the adapter-targetamplification products to produce a plurality of first-strand sequencingreads and a plurality of second-strand sequencing reads; (d) comparingthe first-strand sequencing reads with the second-strand sequencingreads for each of a plurality of the adapter-target complexes; and (e)generating error-corrected sequences for each of a plurality of thedouble-stranded cfDNA molecules by distinguishing erroneous nucleotidesin one strand that lack a matched base change in the complementarystrand.
 22. The method of claim 21, wherein the identifier sequence is arandom identifier sequence.
 23. The method of claim 21, wherein theidentifier sequence is not completely random.
 24. The method of claim21, wherein the identifier sequence is at an end of the partiallydouble-stranded adapter.
 25. The method of claim 21, wherein theidentifier sequence is about 5 to about 20 nucleotides in length. 26.The method of claim 25, wherein the identifier sequence is 5 to 10nucleotides in length.
 27. The method of claim 21, wherein the cfDNA endsequences comprise 10 terminal nucleotides of the double-stranded cfDNAmolecules.
 28. The method of claim 21, wherein the erroneous nucleotidescomprise a polymerase error that arose during amplification orsequencing.
 29. The method of claim 21, further comprising identifying atrue mutation that is present in both strands of one of thedouble-stranded cfDNA molecules.
 30. The method of claim 29, wherein thetrue mutation is identified when it is present in substantially allfirst-strand sequencing reads and second-strand sequencing reads for thedouble-stranded cfDNA molecule.
 31. The method of claim 30, wherein thetrue mutation is identified when it is present in all first-strandsequencing reads and second-strand sequencing reads for thedouble-stranded cfDNA molecule.
 32. The method of claim 21, whereingenerating error-corrected sequences comprises comparing thefirst-strand sequencing reads with the second-strand sequencing readswithin each of a plurality of groups of reads, wherein the groups ofreads are distinguishable by the different pairs of tags.
 33. The methodof claim 21, wherein the cfDNA molecules are isolated from a bloodsample of a subject.
 34. The method of claim 21, wherein the cfDNAmolecules are isolated from a subject having cancer.
 35. The method ofclaim 21, further comprising detecting a cfDNA molecule from a cancer.36. A method of sequencing double-stranded cell-free DNA (cfDNA)molecules, the method comprising: (a) ligating adapters to both ends ofthe double-stranded cfDNA molecules to form adapter-target complexes,wherein (i) the adapters each comprise a double-stranded identifiersequence, (ii) at least two adapters comprise the same identifiersequence and are ligated to different cfDNA molecules, and (iii) cfDNAend sequences together with associated identifier sequences form tags atboth ends of the cfDNA molecules; and (iv) individual adapter-targetcomplexes comprise different pairs of tags; (b) amplifying theadapter-target complexes to produce a plurality of adapter-targetamplification products from each of a first strand and a complementarysecond strand of the adapter-target complexes; (c) sequencing theadapter-target amplification products to produce a plurality offirst-strand sequencing reads and a plurality of second-strandsequencing reads; (d) comparing the first-strand sequencing reads withthe second-strand sequencing reads for each of a plurality of theadapter-target complexes; and (e) generating error-corrected sequencesfor each of a plurality of the double-stranded cfDNA molecules bydistinguishing erroneous nucleotides in the first strand that lack amatched base change in the complementary second strand.
 37. The methodof claim 36, wherein the identifier sequence is a random identifiersequence.
 38. The method of claim 36, wherein the identifier sequence isnot completely random.
 39. The method of claim 36, wherein theidentifier sequence is at an end of the adapter.
 40. The method of claim36, wherein the identifier sequence is about 3 to about 20 nucleotidesin length.
 41. The method of claim 40, wherein the identifier sequenceis 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20nucleotides in length.
 42. The method of claim 40, wherein theidentifier sequence is 5, 6, 7, 8, 9, or 10 nucleotides in length. 43.The method of claim 40, wherein the identifier sequence is about 5 toabout 20 nucleotides in length.
 44. The method of claim 36, wherein theidentifier sequence is 1, 2, 3, 4, 6, 7 or 8 nucleotides in length. 45.The method of claim 36, wherein the cfDNA end sequences comprise 10terminal nucleotides of the double-stranded cfDNA molecules.
 46. Themethod of claim 36, wherein the erroneous nucleotides comprise apolymerase error that arose during amplification or sequencing.
 47. Themethod of claim 36, further comprising identifying a true mutation as amutation that is present in both the first strand and the complementarysecond strand of one of the double-stranded cfDNA molecules.
 48. Themethod of claim 47, wherein the true mutation is identified when it ispresent in substantially all first-strand sequencing reads andsecond-strand sequencing reads for the double-stranded cfDNA molecule.49. The method of claim 48, wherein the true mutation is identified whenit is present in all first-strand sequencing reads and second-strandsequencing reads for the double-stranded cfDNA molecule.
 50. The methodof claim 36, wherein generating error-corrected sequences comprisescomparing the first-strand sequencing reads with the second-strandsequencing reads within each of a plurality of groups of reads, whereinthe groups of reads are distinguishable by the different pairs of tags.51. The method of claim 36, wherein the cfDNA molecules are isolatedfrom a blood sample of a subject.
 52. The method of claim 36, whereinthe cfDNA molecules are isolated from a subject having cancer.
 53. Themethod of claim 36, further comprising detecting a cfDNA molecule from acancer.